| Preface |
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xxi | |
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xxiii | |
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xxix | |
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xxxv | |
| Part I Applied Probability |
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From Dams to Telecommunication - A Survey of Basic Models |
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3 | (10) |
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3 | (1) |
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Moran's Model for the Finite Dam |
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4 | (2) |
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A Continuous Time Model for the Dam |
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6 | (2) |
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A Model for Data Communication Systems |
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8 | (5) |
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11 | (2) |
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Maximum Likelihood Estimation in Queueing Systems |
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13 | (34) |
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13 | (2) |
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M.L.E. in Markovian Systems |
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15 | (1) |
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M.L.E. in Non-Markovian Systems |
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16 | (2) |
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M.L.R. for Single Server Queues Using Waiting Time Data |
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18 | (1) |
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19 | (2) |
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M.L.E. in M/G/1 Using Queue Length Data |
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21 | (3) |
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M.L.E. in GI/M/1 Using Queue Length Data |
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24 | (2) |
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26 | (6) |
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27 | (5) |
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Numerical Evaluation of State Probabilities at Different Epochs in Multiserver GI/Geom/m Queue |
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32 | (1) |
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Model and Solution: GI/Geom/m (EAS) |
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33 | (6) |
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Evaluation of {Qn}∞ from {Qn}∞ |
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37 | (2) |
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Outside observer's distribution |
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39 | (1) |
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39 | (4) |
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Evaluation of {Pn}∞ from {Pn}∞ |
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42 | (1) |
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Outside observer's distribution |
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42 | (1) |
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43 | (4) |
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46 | (1) |
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Busy Period Analysis of GIbIM/1/N Queues - Lattice Path Approach |
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47 | (40) |
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47 | (2) |
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49 | (1) |
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50 | (1) |
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Discretized Cb2/M/1/N Model |
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51 | (9) |
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51 | (1) |
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Counting of Lattice Paths |
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52 | (1) |
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53 | (7) |
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Busy Period Probability for the Discretized Cb2/M/1/N Model |
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60 | (3) |
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Continuous Cb2/M/1/N Model |
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63 | (1) |
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64 | (1) |
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Numerical Computations and Comments |
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65 | (22) |
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67 | (20) |
| Part II Models and Applications |
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Measures for Distributional Classification and Model Selection |
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87 | (14) |
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87 | (1) |
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Current Measures for Distributional Morphology |
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88 | (3) |
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91 | (2) |
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Asymptotic Distributions of J1, J2 |
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93 | (2) |
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95 | (6) |
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97 | (4) |
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Modeling with a Bivariate Geometric Distribution |
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101 | (12) |
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101 | (1) |
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Interpretation of BVG Model Assumptions |
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102 | (2) |
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The Model Under the Environmental Effect |
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104 | (1) |
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Data Analysis with BVG Model |
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105 | (8) |
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109 | (4) |
| Part III Estimation and Testing |
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Small Area Estimation: Updates With Appraisal |
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113 | (28) |
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113 | (2) |
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115 | (5) |
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115 | (3) |
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118 | (2) |
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120 | (8) |
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121 | (3) |
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124 | (1) |
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125 | (3) |
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128 | (13) |
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128 | (3) |
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131 | (10) |
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Unimodality in Circular Data: A Bayes Test |
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141 | (18) |
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141 | (2) |
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143 | (1) |
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Mixture of Two Von-Mises Distributions |
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144 | (2) |
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146 | (1) |
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Prior and Posterior Probability of Unimodality |
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147 | (1) |
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148 | (1) |
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149 | (2) |
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151 | (8) |
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153 | (6) |
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Maximum Likelihood Estimation of the Laplace Parameters Based on Progressive Type-II Censored Samples |
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159 | (10) |
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159 | (2) |
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Examining the Likelihood Function |
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161 | (2) |
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163 | (2) |
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165 | (4) |
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166 | (3) |
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Estimation of Parameters of the Laplace Distribution Using Ranked Set Sampling Procedures |
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169 | (14) |
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169 | (2) |
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Estimation of Parameters Based on Three Procedures |
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171 | (3) |
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171 | (1) |
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Modified Ranked Set Sampling |
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172 | (1) |
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173 | (1) |
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174 | (2) |
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176 | (7) |
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Joint Estimation of μ and σ |
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176 | (1) |
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177 | (1) |
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177 | (1) |
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178 | (5) |
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Some Results on Order Statistics Arising in Multiple Testing |
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183 | (14) |
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183 | (2) |
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185 | (2) |
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Results on Ordered Components of a Random Vector |
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187 | (10) |
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191 | (6) |
| Part IV Robust Inference |
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Robust Estimation Via Generalized L-Statistics: Theory, Applications, and Perspectives |
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197 | (22) |
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197 | (3) |
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198 | (2) |
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Basic Formulation of GL-Statistics |
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200 | (3) |
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Representation of GL-Statistics as Statistical Functionals |
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200 | (2) |
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A More General Form of Functional |
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202 | (1) |
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203 | (1) |
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203 | (5) |
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Differentation Methodology |
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203 | (1) |
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The Estimation Error in the U-Empirical Process |
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204 | (1) |
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Extended Glivenko-Cantelli Theory |
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205 | (1) |
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Oscillation Theory, Generalized Order Statistics, and Bahadur Representations |
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206 | (1) |
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Estimation of the Variance of a U-Statistic |
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207 | (1) |
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General Results for U-Statistics |
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208 | (2) |
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Asymptotic Normality and the LIL |
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208 | (1) |
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209 | (1) |
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209 | (1) |
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210 | (1) |
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210 | (9) |
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One-Sample Quantile Type Parameters |
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210 | (2) |
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Two-Sample Location and Scale Problems |
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212 | (1) |
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213 | (1) |
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213 | (1) |
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Robust Estimation of Exponential Scale Parameter |
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213 | (1) |
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214 | (5) |
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A Class of Robust Stepwise Tests For Manova |
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219 | (22) |
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220 | (2) |
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222 | (5) |
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222 | (2) |
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Combining Independent P-Values |
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224 | (1) |
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Modified Step Down Procedure |
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225 | (2) |
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227 | (1) |
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228 | (3) |
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228 | (3) |
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231 | (10) |
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231 | (10) |
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Robust Estimators for the One-Way Variance Components Model |
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241 | (22) |
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241 | (2) |
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Mixed Linear Models and Estimation of Parameters |
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243 | (3) |
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General Mixed Linear Model |
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243 | (1) |
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Maximum Likelihood and Restricted Maximum Likelihood Estimators |
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244 | (1) |
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Robust Versions of ML and REML Estimators |
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245 | (1) |
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Computation of Estimators for the One Way Model |
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246 | (1) |
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Description of the Simulation Experiment |
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246 | (2) |
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Discussion of the Results |
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248 | (1) |
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Biases of the Estimators of σ2 |
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248 | (1) |
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Biases of the Estimators of σ2e |
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248 | (1) |
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MSE's of Estimators of σ2a |
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248 | (1) |
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MSE's of Estimators of σ2e |
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249 | (1) |
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249 | (14) |
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249 | (14) |
| Part V Regression and Design |
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Performance of the PTE Based on the Conflicting W, LR and LM Tests in Regression Model |
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263 | (20) |
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264 | (1) |
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The Tests and Proposed Estimators |
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265 | (2) |
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BIAS, M and Risk of the Estimators |
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267 | (2) |
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Relative Performance of the Estimators |
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269 | (4) |
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Bias Analysis of the Estimators |
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269 | (1) |
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M Analysis of the Estimators |
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270 | (1) |
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Risk Analysis of the Estimators |
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271 | (2) |
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Efficiency Analysis and Recommendations |
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273 | (2) |
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275 | (8) |
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276 | (7) |
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Estimation of Regression and Dispersion Parameters in the Analysis of Proportions |
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283 | (22) |
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284 | (1) |
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285 | (4) |
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The Extended Beta-Binomial Likelihood |
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285 | (1) |
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The Quasi-Likelihood Method |
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286 | (1) |
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Estimation Using quadratic Estimating Equations |
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287 | (2) |
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Asymptotic Relative Efficiency |
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289 | (3) |
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292 | (1) |
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293 | (12) |
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294 | (11) |
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Semiparametric Location-Scale Regression Models For Survival Data |
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305 | (20) |
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306 | (1) |
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Likelihood Function for the Parametric Location-Scale Models |
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307 | (1) |
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Generalized Profile Likelihood |
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308 | (2) |
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Application of Generalized Profile Likelihood to Semiparametric Location-Scale Regression Models |
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308 | (1) |
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Estimation and Large Sample Properties |
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309 | (1) |
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Examples of Semiparametric Location-Scale Regression Models |
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310 | (2) |
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An Example with Censored Survival Data: Primary Biliary Cirrhosis (PBC) Data |
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312 | (13) |
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313 | (1) |
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Appendix: Computation of the Estimates |
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314 | (11) |
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Analysis of Saturated and Super-Saturated Factorial Designs: A Review |
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325 | (24) |
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325 | (2) |
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327 | (4) |
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Orthogonality and Saturation |
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327 | (2) |
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329 | (2) |
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Orthogonal Saturated Designs |
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331 | (9) |
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331 | (2) |
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Simultaneous Stepwise Tests |
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333 | (4) |
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337 | (1) |
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Individual Confidence Intervals |
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338 | (1) |
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Simultaneous Confidence Intervals |
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338 | (1) |
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339 | (1) |
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Non-Orthogonal Saturated Designs |
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340 | (2) |
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Individual Confidence Intervals |
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341 | (1) |
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342 | (1) |
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342 | (7) |
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343 | (6) |
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On Estimating Subject-Treatment Interaction |
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349 | (18) |
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350 | (2) |
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An Estimator of S2D Using Concomitant Information |
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352 | (7) |
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359 | (1) |
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360 | (7) |
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361 | (6) |
| Part VI Sample Size Methodology |
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Advances in Sample Size Methodology for Binary Data Studies-A Review |
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367 | (16) |
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Establishing Therapeutic Equivalence in Parallel Studies |
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367 | (7) |
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Tests under Δ-Formulation (20.2) |
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369 | (2) |
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Tests under Relative Risk Formulation (ψ Formulation) |
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371 | (2) |
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Confidence Bound Method for Δ Formulation |
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373 | (1) |
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Sample Size for Paired Data Studies |
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374 | (9) |
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Testing for Equality of Correlated Proportions |
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375 | (2) |
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Tests for Establishing Equivalence |
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377 | (3) |
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380 | (3) |
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Robustness of a Sample Size Re-Estimation Procedure in Clinical Trials |
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383 | (18) |
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383 | (2) |
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Formulation of the Problem |
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385 | (1) |
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386 | (9) |
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Fixed-Width Confidence Interval Estimation |
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395 | (1) |
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396 | (5) |
| Part VII Applications to Industry |
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Implementation of Statistical Methods in Industry |
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401 | (12) |
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401 | (1) |
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Levels of Statistical Need in Industry |
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402 | (1) |
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Implementation General Issues |
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402 | (2) |
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Implementation Via Training And/Or Consulting |
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404 | (1) |
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Implementation Via Education |
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405 | (1) |
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University-Industry Collaboration |
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406 | (1) |
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University of Waterloo and Industry |
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406 | (3) |
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409 | (4) |
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410 | (3) |
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Sequential Designs Based on Credible Regions |
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413 | (12) |
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413 | (2) |
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Designs for Control Based on H.P.D. Sets |
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415 | (2) |
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An Example of the Use of HPD Designs |
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417 | (1) |
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Designs For R.S.B. Based on C.P. Intervals |
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418 | (2) |
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420 | (5) |
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Appendix: Model Used in Section 23.3 |
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421 | (1) |
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422 | (3) |
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Aging with Laplace Order Conserving Survival Under Perfect Repairs |
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425 | (16) |
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425 | (1) |
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426 | (3) |
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429 | (5) |
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429 | (2) |
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431 | (2) |
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433 | (1) |
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The Discrete Class GD and Its Dual |
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434 | (2) |
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L and LD Aging with Shocks |
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436 | (5) |
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440 | (1) |
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Defect Rate Estimation Using Imperfect Zero-Defect Sampling with Rectification |
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441 | (24) |
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441 | (2) |
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443 | (9) |
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443 | (1) |
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Modification of Greenberg and Stokes Estimators |
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444 | (2) |
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An Empirical Bayes Estimator |
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446 | (2) |
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448 | (2) |
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450 | (2) |
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452 | (2) |
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452 | (2) |
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Suggestions for Further Research |
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454 | (11) |
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Appendix A1: Calculation of the Second Term in Unew,2 |
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455 | (1) |
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Appendix A2: Analytical Expressions for the Bias and MSE |
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456 | (3) |
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459 | (6) |
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Statistics in the Real World-What I've Learnt in My First Year (and a Half) in Industry |
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465 | (12) |
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465 | (2) |
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467 | (1) |
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The Projects That I've Worked on |
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468 | (3) |
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468 | (1) |
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469 | (1) |
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Reliability Issue with a Supplied Part |
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469 | (1) |
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Constructing a Reliability Database |
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470 | (1) |
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Some Surprises Coming to Industry |
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471 | (3) |
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474 | (3) |
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474 | (3) |
| Part VIII Applications to Ecology, Biology and Health |
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Contemporary Challenges and Recent Advances in Ecological and Environmental Sampling |
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477 | (30) |
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Certain Challenges and Advances in Transect Sampling |
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477 | (9) |
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478 | (2) |
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Bivariate Sighting Functions |
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480 | (2) |
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482 | (4) |
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Certain Challenges and Advances in Composite Sampling |
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486 | (9) |
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Estimating Prevalence Using Composites |
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486 | (5) |
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491 | (1) |
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Compositing and Stochastic Monotonicity |
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492 | (3) |
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Certain Challenges and Advances in Adaptive Cluster Sampling |
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495 | (12) |
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Adaptive Sampling and GIS |
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495 | (4) |
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Using Covariate-Species Community Dissimilarity to Guide Sampling |
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499 | (4) |
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503 | (4) |
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The Analysis of Multiple Neural Spike Trains |
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507 | (18) |
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507 | (1) |
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508 | (2) |
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Methods for Detecting Functional Connections |
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510 | (11) |
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510 | (2) |
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Intensity Function Based Methods |
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512 | (1) |
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513 | (3) |
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516 | (2) |
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518 | (3) |
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521 | (4) |
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521 | (4) |
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Some Statistical Issues Involving Multigeneration Cytonuclear Data |
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525 | (22) |
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526 | (1) |
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527 | (11) |
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Sampling Schemes for Multi-Generation Data |
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529 | (1) |
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530 | (1) |
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Application to Gambusia Data |
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531 | (1) |
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Application to Drosophila Melanogaster Data |
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532 | (1) |
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Tests Against a Specific Selection Model |
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532 | (6) |
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Inference for the Selection Coefficients |
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538 | (9) |
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A Multiplicative Fertility Selection Model |
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539 | (1) |
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An Approximate Likelihood |
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539 | (2) |
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Application to Hypotheses Testing |
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541 | (1) |
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541 | (6) |
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The Performance of Estimation Procedures for Cost-Effectiveness Ratios |
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547 | (14) |
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547 | (1) |
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Confidence Intervals for Cer |
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548 | (2) |
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550 | (2) |
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552 | (1) |
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553 | (5) |
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558 | (3) |
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559 | (2) |
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Modeling Time-To-Event Data Using Flowgraph Models |
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561 | (14) |
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561 | (2) |
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Introduction to Flowgraph Modeling |
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563 | (3) |
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Flowgraph Models for Series Systems |
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563 | (1) |
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Flowgraph Models for Parallel Systems |
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564 | (1) |
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Flowgraph Models with Feedback |
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565 | (1) |
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Reliability Application: Hydraulic Pump System |
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566 | (2) |
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Survival Analysis Application: A Feed Forward Model for HIV |
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568 | (2) |
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570 | (5) |
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571 | (4) |
| Part IX Applications to Economics and Management |
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Information Matrix Tests for the Composed Error frontier Model |
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575 | (22) |
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|
|
|
|
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|
575 | (2) |
|
Information Matrix Tests for Frontier Models |
|
|
577 | (7) |
|
The Elements of the IM Test for the Output Model |
|
|
577 | (5) |
|
The Elements of the IM Test for the Cost Model |
|
|
582 | (2) |
|
|
|
584 | (5) |
|
|
|
584 | (1) |
|
Moments Test for the Output Model |
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|
585 | (2) |
|
|
|
587 | (1) |
|
Moments Test for the Cost Model |
|
|
587 | (2) |
|
|
|
589 | (8) |
|
|
|
590 | (2) |
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|
592 | (3) |
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|
|
595 | (2) |
|
Generalized Estimating Equations for Panel Data and Managerial Monitoring in Electric Utilities |
|
|
597 | (1) |
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|
|
The Introduction and Motivation |
|
|
597 | (4) |
|
Glm, Gee & Panel Logit/Probit (Ldv) Models |
|
|
601 | (4) |
|
|
|
605 | (1) |
|
Random Effects Model from Econometrics |
|
|
606 | (1) |
|
Derivation of GEE, the Estimator for β and Standard Errors |
|
|
607 | (2) |
|
Gee Estimation of Ceo Turnover and Three Hypotheses |
|
|
609 | (2) |
|
|
|
611 | (2) |
|
Shareholder and Consumer Wealth Variables for Hypothesis Testing |
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|
613 | (1) |
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|
|
614 | (2) |
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|
|
616 | (1) |
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|
617 | |
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