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14 Error messages 224Model specification: TERM LEVELS GAMMASvariety 56mu 1repl 4 0.100SECTIONS 224 4 1TYPE 0 0 0STRUCT 224 0 0 0 0 0 012 factors defined [max 500].4 variance parameters [max1500]. 2 special structuresFinal parameter values 0.10000 1.0000Last line read was: Repl 1 0 0 0 012 1 242 224 8000Finished: 27 Jul 2005 15:41:53.668 G structure header: Factor, orderFixing the header line, we then get the error messageStructure / Factor mismatchThis arose because repl has 4 levels but we have only declared 2 in the G structuremodel line. The G structure should readrepl 14 0 IDV 0.1The last lines of the output with this error are displayed below.11 column 11 0 0 1 6.3304 1112 mu 12 identity 0.1000Structure for repl has 2 levels definedFault 1 Structure / Factor mismatchLast line read was: 2 0 IDV 0.1 0 0 0 0 0ninerr7 variety id pid raw rep nloc yield latModel specification: TERM LEVELS GAMMASvariety 56mu 1repl 4 0.100SECTIONS 224 4 1TYPE 0 0 1002STRUCT 224 0 0 0 0 0 0
14 Error messages 2252 1 0 5 0 1 012 factors defined [max 500].5 variance parameters [max1500]. 2 special structuresFinal parameter values 0.10000 1.0000 0.10000Last line read was: 2 0 IDV 0.1 0 0 0 0 012 1 242 224 8000Finished: 27 Jul 2005 15:41:57.153 Structure / Factor mismatch8. A misspelt factor name in the predict statementsee Chapter 13The final error in the job is that a factor name is misspelt in the predict statement.This is a non-fatal error. The faulty statement is simply ignored by ASReml andno .pvs file is produced. To rectify this statement correct voriety to variety.9. Forgetting mv in a spatial analysisThe first error message from running part 2 of the job isR structures imply 0 + 242 records:only 224 existChecking the seventh line of the output below, we see that there were 242 recordsread but only 224 were retained for analysis. There are three reasons records aredropped.1. the !FILTER qualifier has been specified,2. the !D transformation qualifier has been specified and3. there are missing values in the response variable and the user has not specifiedthat they be estimated.The last applies here so we must change the model line to read yield ∼ muvariety mv.Folder: C:\data\ex\manexvariety !AQUALIFIERS: !SKIP 1QUALIFIER: !DOPART 2 is activeReading nin.asd FREE FORMAT skipping 1 linesUnivariate analysis of yieldUsing 224 records of 242 readModel term Size #miss #zero MinNon0 Mean MaxNon01 variety 56 0 0 1 28.5000 56
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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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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 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 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
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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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