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Tullibigeal trial i2 1Variogram of residuals 26 Aug 2002 19:03:111.1305140Outer displacementInner displacementFigure 15.6: Sample variogram of the residuals from the AR1×AR1 model for theTullibigeal dataTullibigeal trial i3 1Variogram of residuals 26 Aug 2002 19:03:220.9552970Outer displacementInner displacementFigure 15.7: Sample variogram of the residuals from the AR1×AR1 +pol(column,-1) model for the Tullibigeal data
15 Examples 2713 LogL=-4245.27 S2= 0.10545E+06 665 df4 LogL=-4229.50 S2= 78387. 665 df5 LogL=-4226.02 S2= 75375. 665 df6 LogL=-4225.64 S2= 77373. 665 df7 LogL=-4225.60 S2= 77710. 665 df8 LogL=-4225.60 S2= 77786. 665 df9 LogL=-4225.60 S2= 77806. 665 dfSource Model terms Gamma Component Comp/SE % Cvariety 532 532 1.14370 88986.3 9.91 0 PVariance 670 665 1.00000 77806.0 8.79 0 PResidual AR=AutoR 67 0.671436 0.671436 15.66 0 UResidual AR=AutoR 10 0.266088 0.266088 3.53 0 UAnalysis of Variance NumDF DenDF F_inc Prob7 mu 1 42.5 7073.70
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ASRemlUser GuideRelease 2.0A R Gilm
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Published by:E-mail:Website:VSN Int
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PrefaceiiASReml is one of several u
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ContentsPrefaceiList of TablesxviiL
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Contentsvi3.3 The ASReml data file
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ContentsviiiCombining rows from sep
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Contentsx7.6 Variance structure qua
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Contentsxii12.2 The command line .
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Contentsxiv15 Examples 24115.1 Intr
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List of Tablesxvi7.3 Details of the
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List of Figuresxix15.8 Rice bloodwo
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1 Introduction 21.1 What ASReml can
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1 Introduction 41.4 How to use this
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2 Some theoryThe linear mixed model
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2 Some theory 8laid out in a rectan
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2 Some theory 10product of matrices
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2 Some theory 12where H = R + ZGZ
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2 Some theory 14where y i is the
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2 Some theory 162.4 Combining varia
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2 Some theory 18balanced one-way cl
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2 Some theory 20L, r × p, and l, r
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2 Some theory 22the terms A, B, C,
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2 Some theory 24Kenward and Roger A
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3 A guided tourIntroductionNebraska
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3 A guided tour 28column rectangula
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3 A guided tour 30(see Chapter 2) t
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3 A guided tour 32els. Similarly fo
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3 A guided tour 34mand to run nin89
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3 A guided tour 36* SYNTAX change:
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3 A guided tour 38repl 3 -0.8713 1.
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3 A guided tour 40title linenin all
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4 Data file preparation 424.1 Intro
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4 Data file preparation 44Fixed for
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5 Command file: Reading the data 46
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6 Command file: Specifying theterms
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6 Command file: Specifying the term
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7 Command file: Specifying variance
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8 Command file: Multivariate analys
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9 Command file: Genetic analysisInt
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9 Command file: Genetic analysis 15
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10 Tabulation of the data andpredic
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10 Tabulation of the data and predi
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11 Functions of variancecomponentsI
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11 Functions of variance components
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11 Functions of variance components
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12 Command file: Running the jobInt
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12 Command file: Running the job 17
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13 Description of output filesIntro
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13 Description of output files 190A
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13 Description of output files 192i
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13 Description of output files 194f
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13 Description of output files 196.
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13 Description of output files 198o
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13 Description of output files 200E
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13 Description of output files 202t
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13 Description of output files 204|
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NIN alliance trial 1989 9a 1Residua
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13 Description of output files 208w
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13 Description of output files 210T
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14 Error messagesIntroductionCommon
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14 Error messages 214filename!last
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14 Error messages 216variety !AQUAL
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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
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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 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 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,
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Index 320parameter, 7variance compo
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