Linear models: least squares and alternatives
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Deutsch |
| Veröffentlicht: |
New York [u.a.]
Springer
1999
|
| Ausgabe: | 2. ed. |
| Schriftenreihe: | Springer series in statistics
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008743186&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Literaturverz. S. 403 - 419. - Ab 3. Aufl. u.d.T.: Linear Models and generalizations |
| Umfang: | XV, 427 S. graph. Darst. |
| ISBN: | 0387988483 |
Internformat
MARC
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| 100 | 1 | |a Rao, Calyampudi Radhakrishna |d 1920-2023 |e Verfasser |0 (DE-588)119285924 |4 aut | |
| 245 | 1 | 0 | |a Linear models |b least squares and alternatives |c C. Radhakrishna Rao ; Helge Toutenburg. With contributions by Andreas Fieger |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York [u.a.] |b Springer |c 1999 | |
| 300 | |a XV, 427 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Springer series in statistics | |
| 500 | |a Literaturverz. S. 403 - 419. - Ab 3. Aufl. u.d.T.: Linear Models and generalizations | ||
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| 650 | 7 | |a Lineaire analyse |2 gtt | |
| 650 | 7 | |a Lineaire modellen |2 gtt | |
| 650 | 4 | |a Modèles linéaires (Statistique) | |
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Datensatz im Suchindex
| DE-BY-TUM_call_number | 0102 MAT 620f 2001 A 28185 |
|---|---|
| DE-BY-TUM_katkey | 1156283 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040010568504 |
| _version_ | 1821931837459529729 |
| adam_text | C. RADHAKRISHNA RAO
HELGE TOUTENBURG
LINEAR MODELS
LEAST SQUARES AND ALTERNATIVES
SECOND EDITION
WITH CONTNBUTIONS BY ANDREAS FIEGER
WITH 33 ILLUSTRATIONS
SPRINGER
CONTENTS
PREFAC
E T
O TH
E FIRS
T EDITIO
N V
PREFAC
E T
O TH
E SECON
D EDITIO
N VI
I
1 INTRODUCTIO
N 1
2 LINEA
R MODEL
S 5
2.1 REGRESSION MODELS IN ECONOMETRIC
S 5
2.2 ECONOMETRI
C MODELS 8
2.3 TH
E REDUCED FOR
M 12
2.4 TH
E MULTIVARIAT
E REGRESSION MODEL 14
2.5 TH
E CLASSICAL MULTIVARIAT
E LINEAR REGRESSION MODEL ..
. 17
2.6 TH
E GENERALIZED LINEA
R REGRESSION MODEL 18
2.7 EXERCISES 20
3 TH
E LINEA
R REGRESSIO
N MODE
L 2
3
3.1 TH
E LINEAR MODEL 23
3.2 TH
E PRINCIPL
E OF ORDINAR
Y LEAST SQUARES (OLS) 24
3.3 GEOMETRI
E PROPERTIE
S OF OLS 25
3.4 BEST LINEAR UNBIASE
D ESTIMATIO
N 27
3.4.1 BASIC THEOREM
S 27
3.4.2 LINEA
R ESTIMATOR
S 32
3.4.3 MEAN DISPERSIO
N ERRO
R 33
3.5 ESTIMATIO
N (PREDICTION
) OF TH
E ERRO
R TER
M E AN
D A
2
. . . 34
X CONTENTS
3.6 CLASSICAL REGRESSION UNDE
R NORMA
L ERROR
S 35
3.6.1 TH
E MAXIMUM-LIKELIHOOD (ML) PRINCIPL
E ...
. 36
3.6.2 ML ESTIMATIO
N I
N CLASSICAL NORMA
L REGRESSION . 36
3.7 TESTIN
G LINEAR HYPOTHESE
S 37
3.8 ANALYSI
S OF VARIANC
E AN
D GOODNES
S OF FI
T 44
3.8.1 BIVARIAT
E REGRESSION 44
3.8.2 MULTIPL
E REGRESSION 49
3.8.3 A COMPLE
X EXAMPL
E 53
3.8.4 GRAPHICA
L PRESENTATIO
N 56
3.9 TH
E CANONICA
L FOR
M 57
3.10 METHOD
S FOR DEALIN
G WIT
H MULTICOLLINEARIT
Y 59
3.10.1 PRINCIPA
L COMPONENT
S REGRESSION 59
3.10.2 RIDGE ESTIMATIO
N 60
3.10.3 SHRINKAGE ESTIMATE
S 64
3.10.4 PARTIA
L LEAS
T SQUARE
S 65
3.11 PROJECTIO
N PURSUI
T REGRESSION 68
3.12 TOTA
L LEAS
T SQUARE
S 70
3.13 MINIMA
X ESTIMATIO
N 72
3.13.1 INEQUALIT
Y RESTRICTION
S 72
3.13.2 TH
E MINIMA
X PRINCIPL
E 75
3.14 CENSORED REGRESSION 80
3.14.1 OVERVIEW 80
3.14.2 LAD ESTIMATOR
S AN
D ASYMPTOTI
C NORMALIT
Y ..
. 81
3.14.3 TEST
S OF LINEA
R HYPOTHESE
S 82
3.15 SIMULTANEOU
S CONFIDENCE INTERVAL
S 84
3.16 CONFIDENCE INTERVA
L FOR TH
E RATI
O OF TW
O LINEA
R
PARAMETRI
C FUNCTION
S 85
3.17 NEURA
L NETWORK
S AN
D NONPARAMETRI
C REGRESSION 86
3.18 LOGISTIC REGRESSION AN
D NEURA
L NETWORKS 87
3.19 RESTRICTE
D REGRESSION 88
3.19.1 PROBLE
M OF SELECTION 88
3.19.2 THEOR
Y OF RESTRICTE
D REGRESSION 88
3.19.3 EFFICIENCY OF SELECTION 91
3.19.4 EXPLICI
T SOLUTIO
N I
N SPECIAL CASES 91
3.20 COMPLEMENT
S 93
3.20.1 LINEA
R MODELS WITHOU
T MOMENTS
: EXERCISE ...
. 9
3
3.20.2 NONLINEA
R IMPROVEMENT OF OLS
E FOR
NONNORMA
L DISTURBANCE
S 9
3
3.20.3 A CHARACTERIZATIO
N OF TH
E LEAST SQUARE
S
ESTIMATO
R 94
3.20.4 A CHARACTERIZATIO
N OF TH
E LEAST SQUARE
S
ESTIMATOR
: A LEMM
A 94
3.21 EXERCISES 95
CONTENTS XI
4 TH
E GENERALIZE
D LINEA
R REGRESSIO
N MODE
L 9
7
4.1 OPTIMA
L LINEAR ESTIMATIO
N OF SS 97
4.1.1 I?I-OPTIMA
L ESTIMATOR
S 98
4.1.2 I?
2
-OPTIMA
L ESTIMATOR
S 102
4.1.3 I?
3
-OPTIMA
L ESTIMATOR
S 103
4.2 TH
E AITKE
N ESTIMATO
R 104
4.3 MISSPECIFICATION OF TH
E DISPERSION MATRI
X 106
4.4 HETEROSCEDASTICIT
Y AN
D AUTOREGRESSIO
N 109
4.5 MIXED EFFECTS MODEL: A UNIFIED THEOR
Y OF LINEAR
ESTIMATIO
N 117
4.5.1 MIXED EFFECTS MODEL 117
4.5.2 A BASIC LEMM
A 118
4.5.3 ESTIMATIO
N OF XSS (TH
E FIXE
D EFFECT) 119
4.5.4 PREDICTIO
N OF U(, (TH
E RANDO
M EFFECT) 120
4.5.5 ESTIMATIO
N OF E 120
4.6 REGRESSION-LIKE EQUATION
S IN ECONOMETRIC
S 121
4.6.1 STOCHASTI
C REGRESSION 121
4.6.2 INSTRUMENTA
L VARIABLE ESTIMATO
R 122
4.6.3 SEEMINGLY UNRELATE
D REGRESSIONS 123
4.7 SIMULTANEOU
S PARAMETE
R ESTIMATIO
N BY EMPIRICA
L
BAYES SOLUTIONS 124
4.7.1 OVERVIEW 124
4.7.2 ESTIMATIO
N OF PARAMETER
S FROM DIFFERENT
LINEAR MODELS 126
4.8 SUPPLEMENT
S 130
4.9 GAUSS-MARKOV, AITKEN AN
D RA
O LEAS
T SQUARE
S ESTIMATOR
S 130
4.9.1 GAUSS-MARKOV LEAS
T SQUARE
S 131
4.9.2 AITKEN LEAST SQUARE
S 132
4.9.3 RA
O LEAST SQUARE
S 132
4.10 EXERCISES 134
5 EXAC
T AN
D STOCHASTI
C LINEA
R RESTRICTION
S 13
7
5.1 USE OF PRIO
R INFORMATIO
N 137
5.2 TH
E RESTRICTE
D LEAST-SQUARE
S ESTIMATO
R 138
5.3 STEPWISE INCLUSION OF EXAC
T LINEA
R RESTRICTION
S 141
5.4 BIASED LINEAR RESTRICTION
S AN
D MD
E COMPARISO
N WIT
H
TH
E OLS
E 146
5.5 MD
E MATRI
X COMPARISON
S OF TW
O BIASED ESTIMATOR
S . . 149
5.6 MD
E MATRI
X COMPARISO
N OF TW
O LINEA
R BIASED ESTIMATOR
S 154
5.7 MD
E COMPARISO
N OF TW
O (BIASED) RESTRICTE
D ESTIMATOR
S 156
5.8 STOCHASTI
C LINEAR RESTRICTION
S 163
5.8.1 MIXED ESTIMATO
R 163
5.8.2 ASSUMPTION
S ABOU
T TH
E DISPERSION MATRI
X ...
. 165
5.8.3 BIASED STOCHASTI
C RESTRICTION
S 168
5.9 WEAKENED LINEAR RESTRICTION
S 172
XII CONTENTS
5.9.1 WEAKLY (R, R)-UNBIASEDNES
S 172
5.9.2 OPTIMA
L WEAKLY (R, R)-UNBIASE
D ESTIMATOR
S . . . 173
5.9.3 FEASIBLE ESTIMATORS-OPTIMA
L SUBSTITUTIO
N OF SS IN
SSI(SS,A) 176
5.9.4 RLSE INSTEA
D OF TH
E MIXED ESTIMATO
R 178
5.10 EXERCISES 179
6 PREDICTIO
N PROBLEM
S I
N TH
E GENERALIZE
D REGRESSIO
N MODE
L 18
1
6.1 INTRODUCTIO
N 181
6.2 SOME SIMPLE LINEAR MODELS 181
6.2.1 TH
E CONSTAN
T MEA
N MODEL 181
6.2.2 TH
E LINEA
R TREN
D MODEL 182
6.2.3 POLYNOMIA
L MODELS 183
6.3 TH
E PREDICTIO
N MODEL 184
6.4 OPTIMA
L HETEROGENEOUS PREDICTIO
N 185
6.5 OPTIMA
L HOMOGENEOUS PREDICTIO
N 187
6.6 MD
E MATRI
X COMPARISON
S BETWEE
N OPTIMA
L AN
D
CLASSICAL PREDICTOR
S 190
6.6.1 COMPARISO
N OF CLASSICAL AN
D OPTIMA
L PREDICTIO
N
WIT
H RESPEC
T T
O TH
E Y* SUPERIORIT
Y 193
6.6.2 COMPARISO
N OF CLASSICAL AN
D OPTIMA
L PREDICTOR
S
WIT
H RESPEC
T T
O TH
E X*SS SUPERIORIT
Y 195
6.7 PREDICTIO
N REGIONS 197
6.8 SIMULTANEOU
S PREDICTIO
N OF ACTUA
L AN
D AVERAGE VALUES OF Y 202
6.8.1 SPECIFICATION OF TARGE
T FUNCTIO
N 202
6.8.2 EXAC
T LINEAR RESTRICTION
S 203
6.8.3 MDE
P USING ORDINAR
Y LEAST SQUARES ESTIMATO
R 204
6.8.4 MDE
P USING RESTRICTE
D ESTIMATO
R 204
6.8.5 MDE
P MATRI
X COMPARISO
N 205
6.9 KAIMA
N FILTE
R 205
6.9.1 DYNAMICA
L AN
D OBSERVATIONA
L EQUATION
S 206
6.9.2 SOME THEOREM
S 206
6.9.3 KAIMA
N MODEL 209
6.10 EXERCISES 210
7 SENSITIVIT
Y ANALYSI
S 21
1
7.1 INTRODUCTIO
N 211
7.2 PREDICTIO
N MATRI
X 211
7.3 EFFECT OF SINGLE OBSERVATIO
N ON ESTIMATIO
N OF PARAMETER
S 217
7.3.1 MEASURES BASED O
N RESIDUAI
S 218
7.3.2 ALGEBRAIC CONSEQUENCES OF OMITTIN
G
A
N OBSERVATIO
N 219
7.3.3 DETECTIO
N OF OUTLIER
S 220
7.4 DIAGNOSTIC PLOT
S FOR TESTIN
G TH
E MODEL ASSUMPTION
S . . . 224
7.5 , MEASURES BASED ON TH
E CONFIDENCE ELLIPSOID 225
CONTENTS
XIN
7.6 PARTIA
L REGRESSION PLOT
S . 231
7.7 REGRESSION DIAGNOSTIC
S FOR REMOVING A
N OBSERVATIO
N WIT
H
ANIMATIN
G GRAPHIC
S 233
7.8 EXERCISES 239
8 ANALYSI
S O
F INCOMPLET
E DAT
A SET
S 24
1
8.1 STATISTICA
L METHOD
S WIT
H MISSING DAT
A 242
8.1.1 COMPLET
E CAS
E ANALYSIS 242
8.1.2 AVAILABLE CAS
E ANALYSIS 242
8.1.3 FILLING IN TH
E MISSING VALUES 243
8.1.4 MODEL-BASED PROCEDURE
S 243
8.2 MISSING-DAT
A MECHANISMS 244
8.2.1 MISSING INDICATO
R MATRI
X 244
8.2.2 MISSING COMPLETEL
Y A
T RANDO
M 244
8.2.3 MISSING A
T RANDO
M 244
8.2.4 NONIGNORABL
E NONRESPONS
E 244
8.3 MISSING PATTER
N 244
8.4 MISSING DAT
A IN TH
E RESPONS
E 245
8.4.1 LEAST-SQUARE
S ANALYSIS FOR FILLED-U
P
DATA-YATE
S PROCEDUR
E 246
8.4.2 ANALYSIS OF COVARIANCE-BARTLETT
S METHO
D . . . 247
8.5 SHRINKAGE ESTIMATIO
N BY YATE
S PROCEDUR
E 248
8.5.1 SHRINKAGE ESTIMATOR
S 248
8.5.2 EFFICIENCY PROPERTIE
S 249
8.6 MISSING VALUES I
N TH
E X-MATRI
X 251
8.6.1 GENERA
L MODEL 251
8.6.2 MISSING VALUES AN
D LOSS IN EFFICIENCY 252
8.7 METHOD
S FOR INCOMPLET
E X-MATRICE
S 254
8.7.1 COMPLET
E CASE ANALYSIS 254
8.7.2 AVAILABLE CAS
E ANALYSIS 255
8.7.3 MAXIMUM-LIKELIHOOD METHOD
S 255
8.8 IMPUTATIO
N METHOD
S FOR INCOMPLET
E X-MATRICE
S 256
8.8.1 MAXIMUM-LIKELIHOOD ESTIMATE
S OF MISSING VALUES 257
8.8.2 ZERO-ORDE
R REGRESSION 258
8.8.3 FIRST-ORDE
R REGRESSION 259
8.8.4 MULTIPL
E IMPUTATIO
N 261
8.8.5 WEIGHTED MIXED REGRESSION 261
8.8.6 TH
E TWO-STAG
E WMR
E 266
8.9 ASSUMPTION
S ABOU
T TH
E MISSING MECHANISM 267
8.10 REGRESSION DIAGNOSTICS T
O IDENTIFY NON-MCA
R PROCESSE
S 267
8.10.1 COMPARISO
N OF TH
E MEANS 268
8.10.2 COMPARIN
G TH
E VARIANCE-COVARIANCE MATRICE
S . . 268
8.10.3 DIAGNOSTIC MEASURE
S FROM SENSITIVIT
Y ANALYSIS . 268
8.10.4 DISTRIBUTIO
N OF TH
E MEASURES AN
D TEST PROCEDUR
E 269
8.11 EXERCISES 270
XIV CONTENTS
9 ROBUS
T REGRESSIO
N 27
1
9.1 OVERVIEW 271
9.2 LEAS
T ABSOLUT
E DEVIATIO
N ESTIMATORS-UNIVARIAT
E CASE . 272
9.3 M-ESTIMATES
: UNIVARIAT
E CASE 276
9.4 ASYMPTOTI
C DISTRIBUTION
S OF LAD ESTIMATOR
S 279
9.4.1 UNIVARIAT
E CASE 279
9.4.2 MULTIVARIAT
E CAS
E 280
9.5 GENERA
L M-ESTIMATE
S 281
9.6 TEST
S OF SIGNIFICANCE 285
1
0 MODEL
S FOR CATEGORICA
L RESPONS
E VARIABLE
S 28
9
10.1 GENERALIZED LINEA
R MODELS 289
10.1.1 EXTENSIO
N OF TH
E REGRESSION MODEL 289
10.1.2 STRUCTUR
E OF TH
E GENERALIZED LINEA
R MODEL
. . . . 291
10.1.3 SCORE FUNCTIO
N AN
D INFORMATIO
N MATRI
X 294
10.1.4 MAXIMUM-LIKELIHOOD ESTIMATIO
N 295
10.1.5 TESTIN
G OF HYPOTHESE
S AN
D GOODNES
S OF FI
T ..
. 298
10.1.6 OVERDISPERSIO
N 299
10.1.7 QUAS
I LOGLIKELIHOOD 301
10.2 CONTINGENCY TABLE
S 303
10.2.1 OVERVIEW 303
10.2.2 WAYS OF COMPARIN
G PROPORTION
S 305
10.2.3 SAMPLIN
G I
N TWO-WAY CONTINGENC
Y TABLE
S ..
. 307
10.2.4 LIKELIHOOD FUNCTIO
N AN
D MAXIMUM-LIKELIHOOD ES
-
TIMATE
S 308
10.2.5 TESTIN
G TH
E GOODNES
S OF FI
T 310
10.3 GLM FOR BINAR
Y RESPONS
E 313
10.3.1 LOGIT MODEL
S AN
D LOGISTIC REGRESSION 313
10.3.2 TESTIN
G TH
E MODEL 315
10.3.3 DISTRIBUTIO
N FUNCTIO
N AS A LINK FUNCTIO
N ...
. 316
10.4 LOGIT MODELS FOR CATEGORICA
L DAT
A 317
10.5 GOODNES
S OF FIT-LIKELIHOOD-RATI
O TEST 318
10.6 LOGLINEAR MODELS FOR CATEGORICA
L VARIABLES 319
10.6.1 TWO-WAY CONTINGENC
Y TABLES 319
10.6.2 THREE-WA
Y CONTINGENC
Y TABLE
S 322
10.7 TH
E SPECIAL CAS
E OF BINAR
Y RESPONSE 325
10.8 CODIN
G OF CATEGORICA
L EXPLANATOR
Y VARIABLES 328
10.8.1 DUMM
Y AN
D EFFECT CODIN
G 328
10.8.2 CODIN
G OF RESPONS
E MODELS 331
10.8.3 CODIN
G OF MODEL
S FOR TH
E HAZAR
D RAT
E 332
10.9 EXTENSION
S T
O DEPENDEN
T BINAR
Y VARIABLES 335
10.9.1 OVERVIEW 335
10.9.2 MODELING APPROACHE
S FOR CORRELATE
D RESPONS
E . 337
10.9.3 QUASI-LIKELIHOOD APPROAC
H FOR CORRELATE
D
BINAR
Y RESPONS
E 338
CONTENTS XV
10.9.4 TH
E GE
E METHO
D BY LIAN
G AN
D ZEGER .....
. 339
10.9.5 PROPERTIE
S OF TH
E GE
E ESTIMAT
E SS
G
341
10.9.6 EFFICIENCY OF TH
E GE
E AN
D IE
E METHOD
S 342
10.9.7 CHOICE OF TH
E QUASI-CORRELATIO
N MATRI
X RI(A) . . 343
10.9.8 BIVARIAT
E BINAR
Y CORRELATE
D RESPONS
E VARIABLE
S . 344
10.9.9 TH
E GE
E METHO
D 344
10.9.10 TH
E IE
E METHO
D 346
10.9.11 AN EXAMPL
E FROM TH
E FIELD OF DENTISTR
Y 346
10.9.12 FUELL LIKELIHOOD APPROAC
H FOR MARGINA
L MODELS . 351
10.10 EXERCISES 351
A MATRI
X ALGEBR
A 35
3
A.
L OVERVIEW 353
A.2 TRACE OF A MATRI
X 355
A.3 DETERMINAN
T OF A MATRI
X 356
A.4 INVERSE OF A MATRI
X 358
A.
5 ORTHOGONA
L MATRICE
S 359
A.6 RAN
K OF A MATRI
X 359
A.7 RANG
E AN
D NULL SPACE 360
A.8 EIGENVALUES AN
D EIGENVECTORS 360
A.9 DECOMPOSITIO
N OF MATRICE
S 362
A.10 DEFINITE MATRICE
S AN
D QUADRATI
C FORM
S 365
A.L
L IDEMPOTEN
T MATRICE
S 371
A.12 GENERALIZED INVERSE 372
A.13 PROJECTOR
S 380
A.14 FUNCTION
S OF NORMALL
Y DISTRIBUTE
D VARIABLES 381
A.15 DIFFERENTIATION OF SCALAR FUNCTION
S OF MATRICE
S 384
A.16 MISCELLANEOUS RESULTS
, STOCHASTI
C CONVERGENCE 387
B TABLE
S 39
1
C SOFTWAR
E FOR LINEA
R REGRESSIO
N MODEL
S 39
5
C.
L SOFTWARE 395
C.2 SPECIAL-PURPOS
E SOFTWARE 400
C.3 RESOURCES 401
REFERENCE
S 40
3
INDE
X
42
1
|
| any_adam_object | 1 |
| author | Rao, Calyampudi Radhakrishna 1920-2023 Toutenburg, Helge 1943-2009 |
| author_GND | (DE-588)119285924 (DE-588)107164310 |
| author_facet | Rao, Calyampudi Radhakrishna 1920-2023 Toutenburg, Helge 1943-2009 |
| author_role | aut aut |
| author_sort | Rao, Calyampudi Radhakrishna 1920-2023 |
| author_variant | c r r cr crr h t ht |
| building | Verbundindex |
| bvnumber | BV012847931 |
| callnumber-first | Q - Science |
| callnumber-label | QA279 |
| callnumber-raw | QA279 |
| callnumber-search | QA279 |
| callnumber-sort | QA 3279 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | QH 234 SK 840 |
| classification_tum | MAT 620f |
| ctrlnum | (OCoLC)41002675 (DE-599)BVBBV012847931 |
| dewey-full | 519.5/36 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/36 |
| dewey-search | 519.5/36 |
| dewey-sort | 3519.5 236 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV012847931 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T10:37:16Z |
| institution | BVB |
| isbn | 0387988483 |
| language | German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-008743186 |
| oclc_num | 41002675 |
| open_access_boolean | |
| owner | DE-703 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-824 DE-521 DE-11 DE-188 |
| owner_facet | DE-703 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-824 DE-521 DE-11 DE-188 |
| physical | XV, 427 S. graph. Darst. |
| publishDate | 1999 |
| publishDateSearch | 1999 |
| publishDateSort | 1999 |
| publisher | Springer |
| record_format | marc |
| series2 | Springer series in statistics |
| spellingShingle | Rao, Calyampudi Radhakrishna 1920-2023 Toutenburg, Helge 1943-2009 Linear models least squares and alternatives Kleinste-kwadratenmethode gtt Lineaire analyse gtt Lineaire modellen gtt Modèles linéaires (Statistique) Linear models (Statistics) Statistik (DE-588)4056995-0 gnd Matrizenrechnung (DE-588)4126963-9 gnd Lineares Modell (DE-588)4134827-8 gnd Ökonometrie (DE-588)4132280-0 gnd Statistische Analyse (DE-588)4116599-8 gnd Wirtschaftstheorie (DE-588)4079351-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4126963-9 (DE-588)4134827-8 (DE-588)4132280-0 (DE-588)4116599-8 (DE-588)4079351-5 (DE-588)4035816-1 |
| title | Linear models least squares and alternatives |
| title_auth | Linear models least squares and alternatives |
| title_exact_search | Linear models least squares and alternatives |
| title_full | Linear models least squares and alternatives C. Radhakrishna Rao ; Helge Toutenburg. With contributions by Andreas Fieger |
| title_fullStr | Linear models least squares and alternatives C. Radhakrishna Rao ; Helge Toutenburg. With contributions by Andreas Fieger |
| title_full_unstemmed | Linear models least squares and alternatives C. Radhakrishna Rao ; Helge Toutenburg. With contributions by Andreas Fieger |
| title_short | Linear models |
| title_sort | linear models least squares and alternatives |
| title_sub | least squares and alternatives |
| topic | Kleinste-kwadratenmethode gtt Lineaire analyse gtt Lineaire modellen gtt Modèles linéaires (Statistique) Linear models (Statistics) Statistik (DE-588)4056995-0 gnd Matrizenrechnung (DE-588)4126963-9 gnd Lineares Modell (DE-588)4134827-8 gnd Ökonometrie (DE-588)4132280-0 gnd Statistische Analyse (DE-588)4116599-8 gnd Wirtschaftstheorie (DE-588)4079351-5 gnd Lineare Optimierung (DE-588)4035816-1 gnd |
| topic_facet | Kleinste-kwadratenmethode Lineaire analyse Lineaire modellen Modèles linéaires (Statistique) Linear models (Statistics) Statistik Matrizenrechnung Lineares Modell Ökonometrie Statistische Analyse Wirtschaftstheorie Lineare Optimierung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008743186&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT raocalyampudiradhakrishna linearmodelsleastsquaresandalternatives AT toutenburghelge linearmodelsleastsquaresandalternatives |
Inhaltsverzeichnis
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Teilbibliothek Mathematik & Informatik
| Signatur: |
0102 MAT 620f 2001 A 28185 Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |