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15 Examples 258power model shown in the previous output. The antedependence model modelsΣ by the inverse cholesky decompositionΣ −1 = UDU ′where D is a diagonal matrix and U is a unit upper triangular matrix. Foran antedependence model of order q, then u ij = 0 for j > i + q − 1. Theantedependence model of order 1 has 9 parameters for these data, 5 in D and 4in U. The input is given byy1 y3 y5 y7 y10 ~ Trait tmt Tr.tmt1 2 014 !S2==1Tr 0 ANTE60.1654.65 73.6591.50 123.3 306.489.17 120.2 298.6 431.862.21 83.85 208.3 301.2 379.8The abbreviated output file is1 LogL=-171.501 S2= 1.0000 60 df2 LogL=-170.097 S2= 1.0000 60 df3 LogL=-166.085 S2= 1.0000 60 df4 LogL=-161.335 S2= 1.0000 60 df5 LogL=-160.407 S2= 1.0000 60 df6 LogL=-160.370 S2= 1.0000 60 df7 LogL=-160.369 S2= 1.0000 60 dfSource Model terms Gamma Component Comp/SE % CResidual ANTE=UDU 1 0.268657E-01 0.268657E-01 2.44 0 UResidual ANTE=UDU 1 -0.628413 -0.628413 -2.55 0 UResidual ANTE=UDU 2 0.372801E-01 0.372801E-01 2.41 0 UResidual ANTE=UDU 2 -1.49108 -1.49108 -2.54 0 UResidual ANTE=UDU 3 0.599632E-02 0.599632E-02 2.43 0 UResidual ANTE=UDU 3 -1.28041 -1.28041 -6.19 0 UResidual ANTE=UDU 4 0.789713E-02 0.789713E-02 2.44 0 UResidual ANTE=UDU 4 -0.967815 -0.967815 -15.40 0 UResidual ANTE=UDU 5 0.390635E-01 0.390635E-01 2.45 0 UCovariance/Variance/Correlation Matrix ANTE=UDU’37.20 0.5946 0.3549 0.3114 0.304023.38 41.55 0.5968 0.5237 0.511234.83 61.89 258.9 0.8775 0.856544.58 79.22 331.4 550.8 0.976143.14 76.67 320.7 533.0 541.4Analysis of Variance DF F_inc8 Trait 5 188.84
15 Examples 2591 tmt 1 4.149 Tr.tmt 4 3.91The iterative sequence converged and the antedependence parameter estimatesare printed columnwise by time, the column of U and the element of D. I.e.⎡ ⎤ ⎡⎤0.0269 1 −0.6284 0 0 00.03730 1 −1.4911 0 0D = diag0.0060, U =0 0 1 −1.2804 0.⎢ ⎥ ⎢⎥⎣ 0.0079 ⎦ ⎣ 0 0 0 1 −0.9678 ⎦0.0391 0 0 0 0 1Finally the input and output files for the unstructured model are presented below.The REML estimate of Σ from the ANTE model is used to provide starting values.############input###########y1 y3 y5 y7 y10 ~ Trait tmt Tr.tmt1 2 014 !S2==1Tr 0 US37.2023.38 41.5534.83 61.89 258.944.58 79.22 331.4 550.843.14 76.67 320.7 533.0 541.4############# output############1 LogL=-160.368 S2= 1.0000 60 df2 LogL=-159.027 S2= 1.0000 60 df3 LogL=-158.247 S2= 1.0000 60 df4 LogL=-158.040 S2= 1.0000 60 df5 LogL=-158.036 S2= 1.0000 60 dfSource Model terms Gamma Component Comp/SE % CResidual US=UnStr 1 37.2262 37.2262 2.45 0 UResidual US=UnStr 1 23.3935 23.3935 1.77 0 UResidual US=UnStr 2 41.5195 41.5195 2.45 0 UResidual US=UnStr 1 51.6524 51.6524 1.61 0 UResidual US=UnStr 2 61.9169 61.9169 1.78 0 UResidual US=UnStr 3 259.121 259.121 2.45 0 UResidual US=UnStr 1 70.8113 70.8113 1.54 0 U
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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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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 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 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
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Bibliography 308Gilmour, A. R., Cul
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Bibliography 310Schall, R. (1991).
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IndexABORTASR.NOW, 65FINALASR.NOW,
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Index 314free format, 42functions o
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Index 316!==, 53!>, 53!>=, 53!*, 53
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Index 318!STEP, 71!SUBSET, 71!SUB,
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Index 320parameter, 7variance compo
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