返回列表 发帖

AN INTRODUCTION TO GENERALIZED LINEAR MODELS SECOND ebook 电子书代购

AN INTRODUCTION TO GENERALIZED LINEAR MODELS SECOND ebook 电子书代购

Contents# H' m2 _. _: g) r' S
Preface
0 d; ~) e  {. h$ c. \1 Introduction5 k4 i9 J; j, F) O' f- I# Y! \. ?
1.1 Background1 W+ K' t, q7 d4 u5 p; F
1.2 Scope7 P, Y, R: d  E' k& @; r
1.3 Notation8 T4 \( c  n) d; \* r5 j
1.4 Distributions related to the Normal distribution
6 X3 w+ W) E  V1.5 Quadratic forms+ s# |* ^0 N% l( y- W/ ^9 R
1.6 Estimation
5 {3 j3 [& s! p/ e1.7 Exercises% ]3 f; [1 H7 t' }& g
2 Model Fitting
* _' y! f" d" ]/ k# |* o2.1 Introduction; d2 ]9 g0 D8 w& {0 K: t1 X
2.2 Examples/ x9 T% ?* r4 o; D, C9 x
2.3 Some principles ofstatistica l modelling
; ~9 Y0 u% A/ l* l2.4 Notation and coding for explanatory variables$ f% D$ K7 C; A4 n. c* E
2.5 Exercises7 Q' X5 q6 G8 z7 d' c
3 Exponential Family and Generalized Linear Models! |; t6 x/ n$ H
3.1 Introduction& k7 ]6 Z/ g% _& F; C$ \
3.2 Exponential family of distributions
  m; k" e8 w9 ?- f* r* \! T+ C: `3.3 Properties ofdistribution s in the exponential family, y* Y1 M' q5 Y3 X. T( P
3.4 Generalized linear models7 ]1 }+ n) |2 y2 B/ l3 ?
3.5 Examples1 x" t1 V0 ^0 P. a5 W1 s0 K
3.6 Exercises
. _! j0 n! b" i* ^+ B/ J4 Estimation
! {6 n! W! @$ M/ H( z3 N7 D0 p, r1 s4.1 Introduction5 `% j9 S6 {, [* i' m; l& F
4.2 Example: Failure times for pressure vessels
7 ?0 b! M+ W7 D4 ^; u- |0 B3 X4.3 Maximum likelihood estimation7 V* _8 E- P" v& J0 s& x0 p
4.4 Poisson regression example
% _# U6 X8 t4 t5 Y; z& u4.5 Exercises
/ v1 D+ ^7 o' `5 n" O' I5 Inference
; j4 E' E7 y; q( U; `  {+ x5.1 Introduction
6 }2 m# H' R5 u  o  m5.2 Sampling distribution for score statistics
$ B9 w1 \0 @1 N0 U2 \: N? 2002 by Chapman & Hall/CRC
, O! h  I5 o% ]55 u1 P" D9 t) v- @1 K
5.3 Taylor series approximations' Q, t) H5 g$ q6 q# z
5.4 Sampling distribution for maximum likelihood estimators
  C& A+ k3 ]8 l& E3 `/ G  {5.5 Log-likelihood ratio statistic* C/ F& }5 y6 G- k! ~% w5 Y0 v8 ]
5.6 Sampling distribution for the deviance
# W' b! e7 N1 G/ W: ?5.7 Hypothesis testing- Z0 x7 Y# R5 h! E
5.8 Exercises# o, W4 m: N9 `9 y0 X+ I0 d
6 Normal Linear Models$ L6 h* {3 n! k0 S
6.1 Introduction
6 U2 i9 G) i- K( ~6.2 Basic results
9 R+ W# o( ~5 A& o/ g6.3 Multiple linear regression# l$ |3 ]- @  k$ B1 t
6.4 Analysis of variance- F  U8 G* [' l; ^$ w* ^+ i
6.5 Analysis ofc ovariance+ i) m8 z  H  Q7 L$ P9 r4 h
6.6 General linear models' ^! y' ?, ^6 n: y, O3 F0 R( v
6.7 Exercises
1 s' y- z3 o) u, n" U: Q/ O7 Binary Variables and Logistic Regression
4 L$ p( i: p! r- c' f" d# n7.1 Probability distributions& g! d4 q8 Z% ]5 \' c" a2 h0 T
7.2 Generalized linear models
7 ~$ Y; b# q& j0 M9 C! u, e7.3 Dose response models
; X: D- h/ @) t; ]2 l7.4 General logistic regression model
0 |* P- A, x, A7.5 Goodness offi t statistics
" l) {) N' E% H4 L$ v! P8 w" b7.6 Residuals
( G5 M8 c, _7 R' _* o7.7 Other diagnostics' c, D0 Q3 M# O  U, Y, [
7.8 Example: Senility and WAIS
! [, [8 b, e* u, {; ^# F' B% ?7.9 Exercises
4 y7 u/ M3 }" v. ~! Z5 F6 ?8 Nominal and Ordinal Logistic Regression3 n& x+ ^, i9 z' h9 U( `
8.1 Introduction
9 }* g# m: ?/ T+ `% L1 J* m8.2 Multinomial distribution
' @( J# i3 ^3 {5 ^. n8 Q8.3 Nominal logistic regression
: U/ s" D" J0 b  v6 q0 k; ~, l8.4 Ordinal logistic regression
! K5 g# j1 Y6 m2 n8.5 General comments
4 y/ k' K1 m2 q- h6 e( b8.6 Exercises  [$ ]* O7 n' `  {, `. W6 U) f
9 Count Data, Poisson Regression and Log-Linear Models, r& d1 k' V& C( {
9.1 Introduction
1 q! c; R/ Z. Q9.2 Poisson regression9 W3 W$ e0 l) P& `2 K1 O
9.3 Examples ofco ntingency tables# t8 u& |! n: ?* v: T/ p0 G, Z) q
9.4 Probability models for contingency tables
% }) E, \5 N; n% G  b  a9.5 Log-linear models
% s2 Y) a' o2 r/ {$ t9.6 Inference for log-linear models
! [6 j5 O/ E0 ~3 i0 n) `9.7 Numerical examples3 i3 J1 B# G: R& y6 N* C
9.8 Remarks8 g; m& V: \* x; V
9.9 Exercises
3 @, ?! ^' T" ~' I. C? 2002 by Chapman & Hall/CRC1 v! k& d1 k3 T* _4 P* X; U
6
$ p0 v% G" K: d" Z- ~6 Q/ Q; B# B10 Survival Analysis4 ~/ C6 o! U! Y$ j2 r
10.1 Introduction
* ]. P: r% N- Y/ W# {$ O/ R10.2 Survivor functions and hazard functions
6 s6 I, V+ Q9 j; G  P" ~" I10.3 Empirical survivor function; M4 v( B5 v  Q( k( i  j3 A8 V
10.4 Estimation5 k% O! E$ p2 i* K2 ?
10.5 Inference
' F% [: ?! B! @( l" y$ @; N10.6 Model checking
- G# f. U& u3 R! |10.7 Example: remission times
0 T2 W- J8 e% m& n* Y$ q% d* D10.8 Exercises
: g  D8 q0 n: |6 ^: j; g+ e11 Clustered and Longitudinal Data
$ V# R  M; m' [! A11.1 Introduction
; g3 _* `, H! b3 _) }9 X% d+ h11.2 Example: Recovery from stroke; O2 `( T9 A* q. Y7 M; ^4 @
11.3 Repeated measures models for Normal data; _7 \- m5 O9 ^0 E( _
11.4 Repeated measures models for non-Normal data
2 V6 G1 n3 S7 f11.5 Multilevel models
( j  C- p  o+ m7 N. {# X& ~11.6 Stroke example continued6 w. k0 z: n, Y$ C3 T
11.7 Comments
8 b& @' O/ n- {# v$ M9 e9 U& V11.8 Exercises( R7 \4 O- o' [
Software
! e) ^, y" l. d( M* VReferences
* y4 G  w% w* b- W( q* H! p. I? 2002 by Chapman & Hall/CRC
( F: P& [4 t1 a1 A5 e- u4 i: \% q7
& {+ _+ y* C/ \+ f9 ]Preface! s5 J$ h3 x8 ^; F  o! W
Statistical tools for analyzing data are developing rapidly so that the 19908 C0 m2 w* \) y, i
edition ofthis book is now out ofdate.0 ^9 n" H' e* f9 q* U4 _5 n
The original purpose ofthe book was to present a unified theoretical and% i, L$ o3 r+ T' R8 u: X; j9 V
conceptual framework for statistical modelling in a way that was accessible
, N- W! d. M; a8 qto undergraduate students and researchers in other fields. This new edition1 ]; u  P4 F; U& W- K
has been expanded to include nominal (or multinomial) and ordinal logistic
1 T+ c, o. R# G7 Aregression, survival analysis and analysis oflongitudinal and clustered data.
( V, I9 A' i, Q: O) |Although these topics do not fall strictly within the definition of generalized
/ U8 |4 @6 f5 n' p- J0 f" dlinear models, the underlying principles and methods are very similar and
+ {8 ^4 J8 C% H* t; ttheir inclusion is consistent with the original purpose ofthe book.
$ i) \+ K8 i1 L, v8 @The new edition relies on numerical methods more than the previous edition
2 _/ [0 F: J! e  Tdid. Some ofthe calculations can be performed with a spreadsheet while others
6 f$ L4 J7 T+ K: ^2 l  Erequire statistical software. There is an emphasis on graphical methods for
7 C9 `$ u/ H" [exploratory data analysis, visualizing numerical optimization (for example,
5 |$ P6 g+ B5 I4 V3 F  }5 Wofthe likelihood function) and plotting residuals to check the adequacy of
8 A* O- g+ N* p8 Wmodels.# p7 }( X0 i6 C* U
3 b* i# R. F! t
Introduction% j) k/ b% {3 b( t
1.1 Background4 k- z, i5 L$ ?6 T* o9 O
This book is designed to introduce the reader to generalized linear models;2 ~8 F* h; \- c1 a! p- ]
these provide a unifying framework for many commonly used statistical techniques.- ^8 w9 W7 T$ _1 ?& a1 i' T, f
They also illustrate the ideas ofstatistical modelling.( G6 H! O# l; P- E" |+ z# l
The reader is assumed to have some familiarity with statistical principles
6 I" Z$ T# `7 [. i9 Oand methods. In particular, understanding the concepts ofestimation, sampling
7 l( n1 x8 u9 }1 o( F) H/ cdistributions and hypothesis testing is necessary. Experience in the use# Y9 W8 a; E5 I& h) u
oft-tests, analysis ofv ariance, simple linear regression and chi-squared tests of5 g) l+ k# ]- E$ s- W
independence for two-dimensional contingency tables is assumed. In addition,
* \  r0 q9 t+ g. @0 ^( ksome knowledge ofmatrix algebra and calculus is required.
& O9 B6 C  R8 d0 sThe reader will find it necessary to have access to statistical computing
# R1 C3 N5 s* V8 b$ A6 n3 }facilities. Many statistical programs, languages or packages can now perform
( e! [7 C: N6 [. a5 ]- Othe analyses discussed in this book. Often, however, they do so with a different
* @# D5 ]+ ]: X6 A/ E' uprogram or procedure for each type of analysis so that the unifying structure
% ], w% I$ F  P0 cis not apparent.8 T" H# h' g* S4 X! q
Some programs or languages which have procedures consistent with the
& _0 R8 P( X4 |: x. _- {( X2 V4 happroach used in this book are: Stata, S-PLUS, Glim, Genstat and SYSTAT.1 ]7 k, A, N7 s) R
This list is not comprehensive as appropriate modules are continually
0 d' A( l5 Y* Vbeing added to other programs.
9 m! ~4 ^" I4 |# }+ o. h+ GIn addition, anyone working through this book may find it helpful to be able
! t0 [* P$ u! A8 ~5 f' v* ato use mathematical software that can perform matrix algebra, differentiation) L9 X# f, m1 s0 D# J7 r$ m4 b
and iterative calculations.
& t/ _* k. t/ b$ K) J, W0 A1.2 Scope
  |% B$ J3 Q* u7 z- c$ T6 Y. h. QThe statistical methods considered in this
" G+ J, H& B) I' U
2 w0 C- A; ]( \& o- c  p/ zv威枝7 \9 M+ {6 E# j+ g
8 {; \7 U" T8 a1 |
% H) V/ P7 W6 C+ s; x( T( Q
+ ^; W* C4 y; c5 S5 C' w

1 n5 j2 }( ?* S+ U) R' s. a6 h$ m& f$ E
联系QQ:526781618; U5 X6 {0 m; P! D
* T) x! F0 T5 T
淘宝旺旺:跟朝流走: N7 [# O' A, M% X/ N( T  Y
4 }7 J/ G0 N  [% x0 M; K
有需要的欢迎联系!专业代购电子书
: i7 y1 k! h, q8 F+ C2 c1 m( M+ h7 h2 x0 u& S3 v5 M  h/ ^0 K
, g# s  N) h, f! O1 X7 h

$ X, m) q" c  E% j, N  L/ }+ ^ebook 英文电子书代购

返回列表