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ContentsvIntroduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Direct product structures . . . . . . . . . . . . . . . . . . . . . . . 7Variance structures for the errors: R structures . . . . . . . . . . . 9Variance structures for the random effects: G structures . . . . . . 102.2 Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Estimation of the variance parameters . . . . . . . . . . . . . . . . 11Estimation/prediction of the fixed and random effects . . . . . . . 142.3 What are BLUPs? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.4 Combining variance models . . . . . . . . . . . . . . . . . . . . . . . 162.5 Inference: Random effects . . . . . . . . . . . . . . . . . . . . . . . . 17Tests of hypotheses: variance parameters . . . . . . . . . . . . . . 17Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182.6 Inference: Fixed effects . . . . . . . . . . . . . . . . . . . . . . . . . . 19Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Incremental and Conditional Wald Statistics . . . . . . . . . . . . . 20Kenward and Roger Adjustments . . . . . . . . . . . . . . . . . . 24Approximate stratum variances . . . . . . . . . . . . . . . . . . . . 243 A <strong>guide</strong>d tour 263.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273.2 Nebraska Intrastate Nursery (NIN) field experiment . . . . . . . . . . 27
Contentsvi3.3 The ASReml data file . . . . . . . . . . . . . . . . . . . . . . . . . . 283.4 The ASReml command file . . . . . . . . . . . . . . . . . . . . . . . . 30The title line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Reading the data . . . . . . . . . . . . . . . . . . . . . . . . . . . 31The data file line . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Tabulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Specifying the terms in the mixed model . . . . . . . . . . . . . . 32Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Variance structures . . . . . . . . . . . . . . . . . . . . . . . . . . 333.5 Running the job . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Forming a job template . . . . . . . . . . . . . . . . . . . . . . . 343.6 Description of output files . . . . . . . . . . . . . . . . . . . . . . . . 35The .asr file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35The .sln file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37The .yht file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383.7 Tabulation, predicted values and functions of the variance components 384 Data file preparation 414.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424.2 The data file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42Free format data files . . . . . . . . . . . . . . . . . . . . . . . . . 42
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: ContentsPrefaceiList of TablesxviiL
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
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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
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14 Error messages 220Missing/faulty
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14 Error messages 222Last line read
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14 Error messages 224Model specific
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14 Error messages 226:11 column 11
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14 Error messages 22814.5 Informati
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14 Error messages 230List of warnin
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14 Error messages 232Alphabetical l
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15 Examples 24215.1 IntroductionIn
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15 Examples 244For simple variance
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15 Examples 2460.2_cwt Marvellous 1
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15 Examples 248The input file conta
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15 Examples 250Source Model terms G
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15 Examples 252ltage example 5−3
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15 Examples 254The focus is modelli
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15 Examples 256y1 y3 y5 y7 y10 ~ Tr
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15 Examples 258power model shown in
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15 Examples 260Residual US=UnStr 2
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15 Examples 262the current model).
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15 Examples 264Slate Hall example f
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15 Examples 266Predicted values of
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15 Examples 268wheat.asd !skip 1 !D
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Tullibigeal trial i2 1Variogram of
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15 Examples 272column evaluated at
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15 Examples 274this is for the pair
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15 Examples 276Table 15.8: Estimate
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15 Examples 278(and in fact necessa
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15 Examples 280Tr.run 22 0 US .79 .
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15 Examples 282Interpretation of re
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15 Examples 284The independence of
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15 Examples 286Note that the data f
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15 Examples 288Table 15.11 Orange d
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15 Examples 290217Predicted values
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15 Examples 292105Residual0-5-10200
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15 Examples 294Table 15.13: REML es
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15 Examples 29615*0. #Asreml will e
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15 Examples 298Covariance/Variance/
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15 Examples 300Eigen values 4.382 0
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15 Examples 302Animal modelIn this
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15 Examples 304additive genetic var
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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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