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

Contents8 X2 U2 e6 D8 V4 S& q7 k- n
Preface# x# u' |  @* u: @
1 Introduction
5 |( G# W: B1 L  Y3 E1.1 Background4 i# G/ l- S3 A7 ~  U, I# q
1.2 Scope
: \0 Z+ q# m; a! e" ?0 Q, d1.3 Notation
- ]+ R; ?7 u- q. {6 y7 ]1.4 Distributions related to the Normal distribution
3 g2 C5 u. x' P- h1 x1.5 Quadratic forms, F+ z; I: `" i  c* a4 ]
1.6 Estimation/ z8 Y# L1 ]( a# M& }8 X$ A6 {
1.7 Exercises
! T  z2 Y" M5 F+ T' G2 Model Fitting' g" y; l6 S$ m
2.1 Introduction8 ]" U% C$ j7 a3 B
2.2 Examples2 B* `! A) C9 L% ~; t6 ]+ f% y: ~5 ^
2.3 Some principles ofstatistica l modelling
! q! [5 |0 r) u1 Q3 f  [  a' ]2.4 Notation and coding for explanatory variables
( V9 Y. \: X1 U3 s0 E3 m2.5 Exercises
" ?: U7 R  g# D0 K9 B3 Exponential Family and Generalized Linear Models
. I' j7 ?5 V* c5 P8 r3 |5 s3.1 Introduction, }6 v% ~7 Y0 {! S( T
3.2 Exponential family of distributions9 _/ E; A& n3 d; v
3.3 Properties ofdistribution s in the exponential family
# t  R7 d! u2 M3.4 Generalized linear models
- ^1 y0 B6 n) U+ E* {* E3.5 Examples3 q9 R: z  }0 `7 \; H
3.6 Exercises. f+ s+ U/ E7 h. F6 s: Y
4 Estimation, Q8 S. K1 R3 r6 G6 T# j( @
4.1 Introduction
3 R) n: D( Y1 W4.2 Example: Failure times for pressure vessels7 h3 T4 Z4 l" K( j6 @9 {! p* _
4.3 Maximum likelihood estimation/ ^8 B% ]4 }0 t- z+ z
4.4 Poisson regression example8 O5 Q) a3 ?9 k1 U! v
4.5 Exercises
/ R0 x. C: z( H5 N5 C! ^- S5 Inference" l3 p, o8 @, N% o/ L$ \. J) _
5.1 Introduction
9 \6 W+ [6 |8 i& E5.2 Sampling distribution for score statistics
  i* h0 V$ V* o% x, H% x; u? 2002 by Chapman & Hall/CRC# K6 K( p' v$ `7 L7 ?( `7 x( B
5( n) o! B) u1 e5 e3 l
5.3 Taylor series approximations; @7 j# j3 u8 ]  l5 i+ @% g6 I
5.4 Sampling distribution for maximum likelihood estimators
2 H+ |( F9 E( T! e" }5.5 Log-likelihood ratio statistic" U3 d4 L+ o# N% @$ t- R  J
5.6 Sampling distribution for the deviance
5 n/ W8 ]1 q0 j8 d+ }9 S$ M- x5.7 Hypothesis testing
7 d/ U' C( C4 `4 n5.8 Exercises
0 t5 O+ t+ Q' l6 Normal Linear Models
/ r$ x4 X7 |+ |6 ]. _! `2 Q6.1 Introduction
8 ^5 n' m3 o" Q: N5 \% X6.2 Basic results
8 u9 p1 h/ X" f5 X! u4 p/ B/ V6.3 Multiple linear regression' v$ O/ [& Q3 V7 D
6.4 Analysis of variance. L/ h( F- U0 ~) Z  I  V
6.5 Analysis ofc ovariance1 w8 `' c  t* B: a
6.6 General linear models
5 h  d- G' c) r+ T$ }0 {& C6.7 Exercises" z. V) w: T0 v% h
7 Binary Variables and Logistic Regression
; Q3 S3 {: k  D0 N" G& o% q; {) D8 y7.1 Probability distributions
* F$ T  y2 n$ g5 h" T6 i! g( D" a" b7.2 Generalized linear models
9 P. N, Z/ R+ \/ j- s' A! ~7.3 Dose response models% P' ?6 E: N: Z5 k
7.4 General logistic regression model
" ^% }, z5 n. e7 h. T! v$ A8 e; s& j7.5 Goodness offi t statistics  b/ B4 p1 C* |- {
7.6 Residuals) Z7 ]% {2 D) `# K' t4 @( l
7.7 Other diagnostics, V2 \/ G& `( Y' q4 D
7.8 Example: Senility and WAIS
3 I$ A, Y  j9 L) k7 V! [1 Q! m7.9 Exercises
7 P4 D! o3 j3 z. z8 Nominal and Ordinal Logistic Regression
: Y& K" b! L4 P0 k/ n8.1 Introduction
1 ]7 K/ @: ~4 G. w1 t+ o8.2 Multinomial distribution
! _& N7 q! m3 ?1 W! s# a8.3 Nominal logistic regression
% C" V/ B7 T; B$ H& {) I8.4 Ordinal logistic regression" {, p+ c" s- p: F/ W
8.5 General comments, t- D/ s) Q- A2 }
8.6 Exercises  z$ a. i, q1 [. b+ F  r
9 Count Data, Poisson Regression and Log-Linear Models
; i( X- v3 ?- K9.1 Introduction1 X# k5 _: B7 A! \0 v- [" r) h
9.2 Poisson regression# ?, M4 y- j! F( }+ F! Z; L
9.3 Examples ofco ntingency tables9 F$ t6 `7 O9 {: y, e
9.4 Probability models for contingency tables1 j/ Z4 U* o# }6 E2 p% z! ~0 O5 F$ E. |
9.5 Log-linear models" K9 `9 [5 g+ B5 s+ u
9.6 Inference for log-linear models
4 j- B$ Z$ r9 O9.7 Numerical examples
4 `  k" ^4 V7 ~$ q3 M0 N9 T9.8 Remarks
5 t/ c6 ?2 S  K2 R: Z9.9 Exercises
; W: a! ^+ E& T: C* y# x? 2002 by Chapman & Hall/CRC' Y7 u+ H# O" N% `5 b
6
+ q; H2 [% ~" s10 Survival Analysis
' i$ M; _2 v% ^; m10.1 Introduction
$ P0 {" e  o- G0 ~) R2 W$ @, M/ e; I10.2 Survivor functions and hazard functions
# ^- L3 A8 Z. X; K10.3 Empirical survivor function  y. D7 s7 C( ^- ]
10.4 Estimation; J# ^7 Z+ ]/ g# V- Q
10.5 Inference- t' a; `9 P* j* o8 W) S
10.6 Model checking
7 r* X$ b( Y! T; g10.7 Example: remission times
: r2 S$ P! i0 A% x9 E10.8 Exercises: p2 t$ o  W( H# w0 X6 o
11 Clustered and Longitudinal Data2 }" m' Q6 o5 P$ z& k4 l
11.1 Introduction
7 V+ s7 ]. l1 N7 |; j5 @* i11.2 Example: Recovery from stroke+ f- R/ g  r' ^  ^
11.3 Repeated measures models for Normal data
. j5 w  }  t7 R9 o- t* c6 C/ s11.4 Repeated measures models for non-Normal data
3 a9 j5 m1 D* e# l5 ]& u11.5 Multilevel models2 L2 _# ]/ Y. c: _4 @$ E4 }# Y+ ]
11.6 Stroke example continued
5 r; K# s+ a5 X; ~11.7 Comments
; K. i* q6 B6 I& y1 s4 W11.8 Exercises
& s# r$ P0 F" kSoftware) Q+ u. r, F+ A2 n1 g. @8 [& P
References: r. m% J2 J8 b1 ?* Z. @9 W! r
? 2002 by Chapman & Hall/CRC
% u& Z! H6 B. W* u% w% q7
6 ]9 T4 A4 M5 {9 ~9 z% lPreface# T0 F9 D2 V8 A& t' t* u
Statistical tools for analyzing data are developing rapidly so that the 19904 }5 F. X: q5 v3 K* g( n* x4 `
edition ofthis book is now out ofdate.0 r1 a7 }$ W" A" |2 e, a
The original purpose ofthe book was to present a unified theoretical and
% f; t$ g& _: t" j6 t/ qconceptual framework for statistical modelling in a way that was accessible0 \3 u- h0 F: Q* A
to undergraduate students and researchers in other fields. This new edition
* R/ U. F$ {& M6 b7 Nhas been expanded to include nominal (or multinomial) and ordinal logistic
% a* |& ~- {/ {) @9 w+ q  F1 oregression, survival analysis and analysis oflongitudinal and clustered data.
/ J3 q- K7 ~! n8 XAlthough these topics do not fall strictly within the definition of generalized4 _) W; R+ E" Q3 @
linear models, the underlying principles and methods are very similar and
( Z2 O: ?3 M  l' Otheir inclusion is consistent with the original purpose ofthe book.( V8 {' F; G! X1 Q* K
The new edition relies on numerical methods more than the previous edition
% U$ {* Z! z$ s& Edid. Some ofthe calculations can be performed with a spreadsheet while others
" E8 W. E: p/ }require statistical software. There is an emphasis on graphical methods for4 U3 r1 b9 g7 P" F( M: ^- X1 A  K
exploratory data analysis, visualizing numerical optimization (for example,
6 J* T2 J3 q( f; E/ h/ Dofthe likelihood function) and plotting residuals to check the adequacy of+ f3 w, [6 Z, m+ {
models.
5 Y! w& ?7 n9 `; D. e" Q$ C9 Q0 l! E/ o
Introduction) f% u% Y9 M- @7 z: ]
1.1 Background
1 d8 ^# L* a) ]5 M- _This book is designed to introduce the reader to generalized linear models;
3 G! M; r3 B; ?2 p9 lthese provide a unifying framework for many commonly used statistical techniques.2 e" t8 t4 A+ i" }& D
They also illustrate the ideas ofstatistical modelling." O6 {( S  v+ O0 ~( _
The reader is assumed to have some familiarity with statistical principles3 ~: i0 v0 m: z( Z2 [1 @
and methods. In particular, understanding the concepts ofestimation, sampling9 o/ X( V! [1 p) g/ U. Y, k
distributions and hypothesis testing is necessary. Experience in the use$ _* X) M4 {8 U, l
oft-tests, analysis ofv ariance, simple linear regression and chi-squared tests of
) l9 s" d* K* g# Eindependence for two-dimensional contingency tables is assumed. In addition,
; l7 M9 e3 I+ [2 \some knowledge ofmatrix algebra and calculus is required., i( M$ T' e) a$ E8 e# o9 T
The reader will find it necessary to have access to statistical computing+ e4 c4 m; K  p1 q- b
facilities. Many statistical programs, languages or packages can now perform
0 s% L. w% W* V8 bthe analyses discussed in this book. Often, however, they do so with a different
  ~; `- o* e) v+ oprogram or procedure for each type of analysis so that the unifying structure
: H) d& p" g" V# x3 yis not apparent.
* u# b$ A$ g- o! D* u3 QSome programs or languages which have procedures consistent with the
; Z& P6 d( R% @  r; y7 sapproach used in this book are: Stata, S-PLUS, Glim, Genstat and SYSTAT.
7 N  m' |. p, @' PThis list is not comprehensive as appropriate modules are continually
* w) F' Y6 _; l: S; qbeing added to other programs.& Y6 a( @# R* c3 j
In addition, anyone working through this book may find it helpful to be able3 C; t+ v5 I) b( B1 a
to use mathematical software that can perform matrix algebra, differentiation, U( R9 q4 l' Y  v
and iterative calculations.
$ r9 A# Z) C: Z, M: ?4 t. k8 D  i( C4 O1.2 Scope1 Y0 q; G' u3 t3 w3 {6 S
The statistical methods considered in this
+ g2 F) {9 v3 w/ G7 `. _% n3 P# G5 X3 p0 x: ]) a
v威枝
+ y( Q. R. [7 P: t, q; w9 \' Y, M0 {' i' C1 V
7 l1 D6 A1 y. _" _8 @
4 \0 h1 o4 O# n- ]4 p

1 J! f6 m6 m+ [: W+ F: J1 x( [/ W+ t
联系QQ:526781618
" A, M0 U" `. N* B+ G- B1 T, o3 p" z& m* u9 d, i
淘宝旺旺:跟朝流走
( J* r, x; s0 |( }8 H* L3 B' F5 l) f. m3 h. G3 K% o2 j
有需要的欢迎联系!专业代购电子书
* e' @3 C/ B4 C* z  L% I# V. D- T+ H9 E* r% K5 f
/ U, Q) h! Q% L# |$ H, Y
( c9 a/ L  L+ |4 ~0 L5 o# i" w
ebook 英文电子书代购

返回列表