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13 Description of output files 208where ˜β Dis the dense portion of β and C DD is the dense portion of C −1 . Thisis the first 20 rows of nin89a.vrb. Note that the first element is the estimatederror variance, that is, 48.6802, see the variance component estimates in the .asroutput.0.486802E + 02 0.000000E + 00 0.000000E + 00 0.298660E + 01 0.000000E + 000.807551E + 01 0.470711E + 01 0.000000E + 00 0.456648E + 01 0.886687E + 01−0.313123E + 00 0.000000E + 00 0.410031E + 01 0.476546E + 01 0.876708E + 010.295404E + 01 0.000000E + 00 0.343331E + 01 0.389620E + 01 0.416124E + 010.743616E + 01 0.163302E + 01 0.000000E + 00 0.377176E + 01 0.428109E + 010.472519E + 01 0.402696E + 01 0.837281E + 01 0.129013E + 01 0.000000E + 000.330076E + 01 0.347471E + 01 0.357605E + 01 0.316915E + 01 0.412130E + 010.768275E + 01 0.310018E + 00 0.000000E + 00 0.376637E + 01 0.419780E + 010.395693E + 01 0.383429E + 01 0.458492E + 01 0.378585E + 01 0.985202E + 010.226478E + 01 0.000000E + 00 0.379286E + 01 0.442457E + 01 0.439485E + 010.402503E + 01 0.440539E + 01 0.362391E + 01 0.502071E + 01 0.901191E + 010.508553E + 01 0.000000E + 00 0.393626E + 01 0.430512E + 01 0.423753E + 010.428826E + 01 0.417864E + 01 0.363341E + 01 0.444776E + 01 0.527289E + 010.855241E + 01 0.243687E + 01 0.000000E + 00 0.351386E + 01 0.369983E + 010.384055E + 01 0.330171E + 01 0.362019E + 01 0.352370E + 01 0.359516E + 010.392097E + 01 0.406762E + 01 0.801579E + 01 0.475935E + 01 0.000000E + 00...The first 5 rows of the lower triangular matrix in this case are⎡⎢⎣48.68020 02.98660 0 8.075514.70711 0 4.56648 8.86687−0.313123 0 4.10031 4.76546 8.76708.....⎤⎥⎦. ..The .vvp fileThe .vvp file contains the inverse of the average information matrix on the componentsscale. The file is formatted for reading back under the control of the.pin file described in Chapter 11. The matrix is lower triangular row-wise in theorder the parameters are printed in the .asr file. This is nin89a.vvp with theparameter estimates in the order error variance, spatial row correlation, spatialcolumn correlation.Variance of Variance components 351.08520.217089 0.318058E-020.677748E-01 -0.201181E-02 0.649355E-02
13 Description of output files 20913.5 ASReml output objects and where to find themTable 13.2 presents a list of objects produced with each ASReml run and whereto find them in the output files.Table 13.2: ASReml output objects and where to find themoutput object found in commentanalysis of variancetabledata summaryeigen analysiselapsed timefixed and random effects.asr file.asr file.ass file.res file.asl file.asr file.asl file.sln filethe analysis of variance table contains F-statisticsfor each term in the fixed part of the model. Theseprovide for an incremental or optionally a conditionaltest of significance (see Section 6.12).includes the number of records read and retainedfor analysis, the minimum, mean, maximum,number of zeros, number of missing values perdata field, factor/variate field distinction.An extended report of the data is written to the.ass file if the !SUM qualifier is specified. It includescell counts for factors, histograms of variatesand simple correlations among variatesWhen ASReml reports a variance matrix to the.asr file, it also reports an eigen analysis of thematrix (eigen values and eigen vectors) to the.res file.this can be determined by comparing the starttime with the finishing time.The execution times for parts of the Iteration processare written to the .asl file if the !DEBUG!LOGFILE command line qualifiers are invoked.if !BRIEF -1 is invoked, the effects that were includedin the dense portion of the solution are alsoprinted in the .asr file with their standard error,a t-statistic for testing that effect and a t-statisticfor testing it against the preceding effect in thatfactor.heritability .pvc file placed in the .pvc file when postprocessing witha .pin filehistogram of residuals.res fileand graphics fileintermediate results .asl file given if the -DL command line option is used.
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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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Page 210 and 211: 13 Description of output filesIntro
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Page 228 and 229: 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
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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
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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
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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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