Download pdf guide - VSN International

More documents

Recommendations

Info

7 Command file: Specifying variance structures 116Table 7.2: Schematic outline of variance model specification in ASRemlgeneral syntax model 4variance header line [s [c [g]]] 1 2 1- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -R structure definition lines S 1 C 1 11 column AR1 0.3C 2 22 row AR1 0.3..C c -S 2 C 1.C c..S s C 1.C c- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -G structure definition lines G 1 repl 14 0 IDV 0.1-.-.-.-G 2 -..G g -
7 Command file: Specifying variance structures 117Variance header lineThe variance header line is of the form[s [c [g]]]• s and c relate to the R structures, g is thenumber of G structures,• the variance header line may be omittedif the default IID R structure is required,no G structures are being explicitly definedand there are no parameter constraints (see!VCC and examples 1 and 2a),• s is used to code the number of independentsections in the error termNIN Alliance Trial 1989variety !Aid.row 22column 11nin89aug.asd !skip 1yield ∼ mu variety !r repl,!f mv1 2 122 row AR1 0.311 column AR1 0.3repl 1repl 0 IDV 0.1– if s = 0, the default IID R structure is assumed and no R structure definitionlines are required (as in examples 2b and 5),– if s > 0, s R structure definitions are required, one for each of the s sections(as in examples 3a, 3b, 3c and 4),– for the analysis of multi-section data s can be replaced by the name of afactor with the appropriate number of levels, one for each section,• c is the number of component variance models involved in the variance structurefor the error term for each section; for example, 3a, 3b and 3c havecolumn.row as the error term and the variance structure for column.row involves2 variance models, the first for column and the second for row,– c has a default value of 2 when s is not specified as zero,• g is the number of variance structures (G structures) that will be explicitlyspecified for the random terms in the model.See Table 7.3See Section 7.7R and G structures are now discussed with reference to s, c and g. As alreadynoted, each variance structure may involve several variance models which relateto the individual terms involved in the random effect or error. For example, atwo factor interaction may have a variance model for each of the two factorsinvolved in the interaction. Variance models are listed in Table 7.3. As indicatedin the discussion of 2b, care must be taken with respect to scale parameters whencombining variance models (see also Section 7.7).
Page 1 and 2:
ASRemlUser GuideRelease 2.0A R Gilm
Page 3 and 4:
Published by:E-mail:Website:VSN Int
Page 5 and 6:
PrefaceiiASReml is one of several u
Page 7 and 8:
ContentsPrefaceiList of TablesxviiL
Page 9 and 10:
Contentsvi3.3 The ASReml data file
Page 11 and 12:
ContentsviiiCombining rows from sep
Page 13 and 14:
Contentsx7.6 Variance structure qua
Page 15 and 16:
Contentsxii12.2 The command line .
Page 17 and 18:
Contentsxiv15 Examples 24115.1 Intr
Page 19:
List of Tablesxvi7.3 Details of the
Page 22 and 23:
List of Figuresxix15.8 Rice bloodwo
Page 24 and 25:
1 Introduction 21.1 What ASReml can
Page 26 and 27:
1 Introduction 41.4 How to use this
Page 28 and 29:
2 Some theoryThe linear mixed model
Page 30 and 31:
2 Some theory 8laid out in a rectan
Page 32 and 33:
2 Some theory 10product of matrices
Page 34 and 35:
2 Some theory 12where H = R + ZGZ
Page 36 and 37:
2 Some theory 14where y i is the
Page 38 and 39:
2 Some theory 162.4 Combining varia
Page 40 and 41:
2 Some theory 18balanced one-way cl
Page 42 and 43:
2 Some theory 20L, r × p, and l, r
Page 44 and 45:
2 Some theory 22the terms A, B, C,
Page 46 and 47:
2 Some theory 24Kenward and Roger A
Page 48 and 49:
3 A guided tourIntroductionNebraska
Page 50 and 51:
3 A guided tour 28column rectangula
Page 52 and 53:
3 A guided tour 30(see Chapter 2) t
Page 54 and 55:
3 A guided tour 32els. Similarly fo
Page 56 and 57:
3 A guided tour 34mand to run nin89
Page 58 and 59:
3 A guided tour 36* SYNTAX change:
Page 60 and 61:
3 A guided tour 38repl 3 -0.8713 1.
Page 62 and 63:
3 A guided tour 40title linenin all
Page 64 and 65:
4 Data file preparation 424.1 Intro
Page 66 and 67:
4 Data file preparation 44Fixed for
Page 68 and 69:
5 Command file: Reading the data 46
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
Page 88 and 89: 5 Command file: Reading the data 66
Page 104 and 105: 6 Command file: Specifying theterms
Page 106 and 107: 6 Command file: Specifying the term
Page 128 and 129: 7 Command file: Specifying variance
Page 164 and 165: 8 Command file: Multivariate analys
Page 170 and 171: 9 Command file: Genetic analysisInt
Page 172 and 173: 9 Command file: Genetic analysis 15
Page 178 and 179: 10 Tabulation of the data andpredic
Page 180 and 181: 10 Tabulation of the data and predi
Page 188 and 189:
10 Tabulation of the data and predi
Page 190 and 191:
10 Tabulation of the data and predi
Page 192 and 193:
11 Functions of variancecomponentsI
Page 194 and 195:
11 Functions of variance components
Page 196 and 197:
11 Functions of variance components
Page 198 and 199:
12 Command file: Running the jobInt
Page 200 and 201:
12 Command file: Running the job 17
Page 202 and 203:
Page 204 and 205:
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
13 Description of output filesIntro
Page 212 and 213:
13 Description of output files 190A
Page 214 and 215:
13 Description of output files 192i
Page 216 and 217:
13 Description of output files 194f
Page 218 and 219:
13 Description of output files 196.
Page 220 and 221:
13 Description of output files 198o
Page 222 and 223:
13 Description of output files 200E
Page 224 and 225:
13 Description of output files 202t
Page 226 and 227:
13 Description of output files 204|
Page 228 and 229:
NIN alliance trial 1989 9a 1Residua
Page 230 and 231:
13 Description of output files 208w
Page 232 and 233:
13 Description of output files 210T
Page 234 and 235:
14 Error messagesIntroductionCommon
Page 236 and 237:
14 Error messages 214filename!last
Page 238 and 239:
14 Error messages 216variety !AQUAL
Page 240 and 241:
14 Error messages 2188. misspelt va
Page 242 and 243:
14 Error messages 220Missing/faulty
Page 244 and 245:
14 Error messages 222Last line read
Page 246 and 247:
14 Error messages 224Model specific
Page 248 and 249:
14 Error messages 226:11 column 11
Page 250 and 251:
14 Error messages 22814.5 Informati
Page 252 and 253:
14 Error messages 230List of warnin
Page 254 and 255:
14 Error messages 232Alphabetical l
Page 256 and 257:
Page 258 and 259:
Page 260 and 261:
Page 262 and 263:
Page 264 and 265:
15 Examples 24215.1 IntroductionIn
Page 266 and 267:
15 Examples 244For simple variance
Page 268 and 269:
15 Examples 2460.2_cwt Marvellous 1
Page 270 and 271:
15 Examples 248The input file conta
Page 272 and 273:
15 Examples 250Source Model terms G
Page 274 and 275:
15 Examples 252ltage example 5−3
Page 276 and 277:
15 Examples 254The focus is modelli
Page 278 and 279:
15 Examples 256y1 y3 y5 y7 y10 ~ Tr
Page 280 and 281:
15 Examples 258power model shown in
Page 282 and 283:
15 Examples 260Residual US=UnStr 2
Page 284 and 285:
15 Examples 262the current model).
Page 286 and 287:
15 Examples 264Slate Hall example f
Page 288 and 289:
15 Examples 266Predicted values of
Page 290 and 291:
15 Examples 268wheat.asd !skip 1 !D
Page 292 and 293:
Tullibigeal trial i2 1Variogram of
Page 294 and 295:
15 Examples 272column evaluated at
Page 296 and 297:
15 Examples 274this is for the pair
Page 298 and 299:
15 Examples 276Table 15.8: Estimate
Page 300 and 301:
15 Examples 278(and in fact necessa
Page 302 and 303:
15 Examples 280Tr.run 22 0 US .79 .
Page 304 and 305:
15 Examples 282Interpretation of re
Page 306 and 307:
15 Examples 284The independence of
Page 308 and 309:
15 Examples 286Note that the data f
Page 310 and 311:
15 Examples 288Table 15.11 Orange d
Page 312 and 313:
15 Examples 290217Predicted values
Page 314 and 315:
15 Examples 292105Residual0-5-10200
Page 316 and 317:
15 Examples 294Table 15.13: REML es
Page 318 and 319:
15 Examples 29615*0. #Asreml will e
Page 320 and 321:
15 Examples 298Covariance/Variance/
Page 322 and 323:
15 Examples 300Eigen values 4.382 0
Page 324 and 325:
15 Examples 302Animal modelIn this
Page 326 and 327:
15 Examples 304additive genetic var
Page 328 and 329:
BibliographyAbramowitz, M. and Steg
Page 330 and 331:
Bibliography 308Gilmour, A. R., Cul
Page 332 and 333:
Bibliography 310Schall, R. (1991).
Page 334 and 335:
IndexABORTASR.NOW, 65FINALASR.NOW,
Page 336 and 337:
Index 314free format, 42functions o
Page 338 and 339:
Index 316!==, 53!>, 53!>=, 53!*, 53
Page 340 and 341:
Index 318!STEP, 71!SUBSET, 71!SUB,
Page 342:
Index 320parameter, 7variance compo
show all

Download pdf guide - VSN International

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?