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Springer Texts in StatisticsAdvisors:George Casella Stephen Fienberg Ingram OlkinSpringerNew YorkBerlinHeidelbergHong KongLondonMilanParisTokyo
Springer Texts in StatisticsAlfrd: Elements of Statistics for the Life and Social SciencesBerger: An Introduction to Probability and Stochastic ProcessesBilodeau and Brenner: Theory of Multivariate StatisticsBlom: Probability and Statistics: Theory and ApplicationsBrockwell and Davis: Introduction to Times Series and Forecasting,Second EditionChow and Teicher: Probability Theory: Independence, Interchangeability,Martingales, Third EditionChrisfensen: Advanced Linear Modeliig: Multivariate, Time Series, andSpatial Data-Nonparamekic Regression and Response SurfaceMaximization, Second EditionChrisfensen: Log-Linear Models and Lagistic Regression, Second EditionChrisfensen: Plane Answers to Complex Questions: The Theory of LinearModels, Third EditionCreighfon: A First Course in Probability Models and Statistical InferenceDavis.' Statistical Methods for the Analysis of Repeated MeasurementsDean and Vow Design and Analysis of Experimentsdu Toif, Sfqn, and Stump$ Graphical Exploratory Data AnalysisDurreft: Essentials of Stochastic ProcessesEdwarak Introduction to Graphical Modelling, Second EditionFinkelstein and Levin: Statistics for LawyersFlury: A First Course in Multivariate StatisticsJobson: Applied Multivariate Data Analysis, Volume I Regression andExperimental DesignJobson: Applied Multivariate Data Analysis, Volume 11: Categorical andMultivariate MethodsKulbjleisch: Probability and Statistical Inference, Volume I: Probability,Second EditionKalbjleisch: Probability and Statistical Inference, Volume 11: Statistical Inference,Second EditionKarr: ProbabilityKqfifz: Applied Mathematical Demography, Second EditionKiefer: Introduction to Statistical InferenceKokoska and Nevison: Statistical Tables and FormulaeKulhrni: Modeling, Analysis, Design, and Control of Stochastic SystemsLunge: Applied ProbabilityLehmann: Elements of Large-Sample TheoryLehmann: Testing statistical Hypotheses, Second EditionLehmann and CareNa: Theory of Point Estimation, Second EditionLindman: Analysis of Variance in Experimental DesignLindsey: Applying Generalized Linear Models(continued aJler index)
Page 1: Applied ProbabilityKenneth LangeSpr
Page 5 and 6: Kenneth IangeDepartment of Biomathe
Page 7 and 8: viPrefacebringing up their children
Page 9 and 10: Preface to the First EditionWhen I
Page 11 and 12: A Few Words about SoftwarePrefacexi
Page 13 and 14: ContentsPreface to the Second Editi
Page 15 and 16: 8.4 Multivariate Traits . . . . . .
Page 17 and 18: 15.2 Review of Diffusion Processes
Page 19 and 20: 2 1. Basic Principles of Population
Page 27 and 28: 10 1. Basic Principles of Populatio
Page 39 and 40: 22 2. Counting Methods and the EM A
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36 2. Counting Methods and the EM A
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38 2. Counting Methods and the EM A
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40 3. Newton’s Method and Scoring
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60 4. Hypothesis Testing and Catego
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5Genetic Identity Coefficients5.1 I
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5. Genetic Identity Coefficients 83
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6Applications of IdentityCoefficien
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Example 6.2.1 Siblings at the ABO L
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6. Applications of Identity Coeffic
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✓✒✏✑✓✒✏✑✓✒✏
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7Computation of MendelianLikelihood
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7. Computation of Mendelian Likelih
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✓✒✓✒✏✑✏✑✓✒✏
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✓✒✓✒✏✑✏✑7. Computat
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✓✒✓✒✏✑✏✑✓✒✓
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142 8. The Polygenic Modelidentity
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144 8. The Polygenic Model(h) If B
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146 8. The Polygenic Modelmatrix E(
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148 8. The Polygenic Modelcovarianc
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150 8. The Polygenic ModelTABLE 8.2
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152 8. The Polygenic Modelare hard
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154 8. The Polygenic Model8.9 The H
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156 8. The Polygenic Modelrecurrenc
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158 8. The Polygenic Model♠✉♠
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160 8. The Polygenic Model(b) Omitt
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162 8. The Polygenic Modelrandom sa
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164 8. The Polygenic ModelTo calcul
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166 8. The Polygenic Model[2] Barnh
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168 8. The Polygenic Model[28] Ott
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170 9. Descent Graph Methods9.2 Rev
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172 9. Descent Graph MethodsConvers
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174 9. Descent Graph Methodsis also
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176 9. Descent Graph Methods❧121/
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178 9. Descent Graph MethodsC D E F
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180 9. Descent Graph Methodsgenetic
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❛ ❛ ❛182 9. Descent Graph Met
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184 9. Descent Graph Methodsgraph C
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186 9. Descent Graph Methodsprocess
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188 9. Descent Graph Methods9.11 Th
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190 9. Descent Graph MethodsThe las
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192 9. Descent Graph Methodssimples
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194 9. Descent Graph Methodsand the
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196 9. Descent Graph Methodslocus t
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198 9. Descent Graph Methods11. For
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200 9. Descent Graph Methods[15] Ke
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10Molecular Phylogeny10.1 Introduct
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10. Molecular Phylogeny 205==(2n
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10. Molecular Phylogeny 207✁❆
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10. Molecular Phylogeny 20910.4 Rev
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10.5 A Nucleotide Substitution Mode
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10. Molecular Phylogeny 213satisfyi
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10. Molecular Phylogeny 215most eco
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10. Molecular Phylogeny 217TABLE 10
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10. Molecular Phylogeny 219reversib
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10. Molecular Phylogeny 221so forth
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10. Molecular Phylogeny 223TABLE 10
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10. Let A and B be the 2 × 2 real
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10. Molecular Phylogeny 227this rev
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10. Molecular Phylogeny 229[14] Lak
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232 11. Radiation Hybrid Mappingon
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234 11. Radiation Hybrid Mapping1 2
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236 11. Radiation Hybrid Mappingpro
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238 11. Radiation Hybrid Mappingpar
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240 11. Radiation Hybrid Mappingtha
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242 11. Radiation Hybrid Mappingvie
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244 11. Radiation Hybrid MappingSim
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246 11. Radiation Hybrid Mappingthe
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248 11. Radiation Hybrid Mappingpri
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250 11. Radiation Hybrid MappingInt
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252 11. Radiation Hybrid MappingSho
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254 11. Radiation Hybrid Mapping[4]
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12Models of Recombination12.1 Intro
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12. Models of Recombination 259dist
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= 1 212. Models of Recombination 26
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12. Models of Recombination 263]+ 2
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12. Models of Recombination 265lies
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12. Models of Recombination 267left
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12. Models of Recombination 269matr
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12. Models of Recombination 271In t
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12.7 Application to Drosophila Data
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12. Models of Recombination 275If G
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12. Models of Recombination 2779. I
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12. Models of Recombination 279[12]
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13Sequence Analysis13.1 Introductio
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13. Sequence Analysis 283using the
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13. Sequence Analysis 285simpler re
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13. Sequence Analysis 287run entire
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13. Sequence Analysis 28913.5 Paral
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13. Sequence Analysis 291gap score
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13. Sequence Analysis 293alignment
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p R s mF (s) =p R s m +(1− s)Q(s)
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13. Sequence Analysis 297[8] Sankof
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300 14. Poisson Approximationin I [
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302 14. Poisson Approximationgene i
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304 14. Poisson Approximationestima
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306 14. Poisson Approximationapprox
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308 14. Poisson ApproximationIt fol
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310 14. Poisson ApproximationThe Ch
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312 14. Poisson Approximationof mat
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314 14. Poisson Approximation10. Co
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316 14. Poisson Approximation[10] G
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318 15. Diffusion Processesrather t
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320 15. Diffusion Processes∫ ∞=
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322 15. Diffusion Processeslation g
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324 15. Diffusion ProcessesIt follo
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326 15. Diffusion Processesfor X 0
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328 15. Diffusion Processes=≈=k 4
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330 15. Diffusion Processesc i+1,k
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332 15. Diffusion Processesc ij→i
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334 15. Diffusion Processesgrown ex
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336 15. Diffusion Processesand the
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338 15. Diffusion Processes11. Supp
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Appendix A: MolecularGenetics in Br
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A.2 From Gene to ProteinAppendix A:
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A.3 Manipulating DNAAppendix A: Mol
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Appendix A: Molecular Genetics in B
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Appendix A: Molecular Genetics in B
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Appendix B: The NormalDistributionB
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matrix I, and characteristic functi
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IndexABO locus, see Blood group loc
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Index 357Coupling × repulsion mati
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Index 359preorder traversal, 208roo
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Index 361relation to disease risk,
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Index 363Meiosis indicators, 189MEN
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Index 365Pulley principle, see Fels
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Index 367Stationary distribution, s
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