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NIN alliance trial 1989 9a 1Residuals V Row and Column position: 14 Jul 2005 12:41:18Range: −24.87 15.91Figure 13.4 Plot of the marginal means of the residualsHistogramNIN allianceof residuals14trial 1989Jul 2005vE_A12:41:18Peak Count: 17Range: −24.87 15.91Figure 13.5 Histogram of residuals0
13 Description of output files 207STRUCTURE 11 1 1 0.437483The .tab fileThe .tab file contains the simple variety means and cell frequencies. Below is anedited version of nin89.tab.nin alliance trial 10 Sep 2002 04:20:15Simple tabulation of yield.varietyLANCER 28.56 4BRULE 26.07 4REDLAND 30.50 4CODY 21.21 4ARAPAHOE 29.44 4NE83404 27.39 4NE83406 24.28 4NE83407 22.69 4CENTURA 21.65 4SCOUT66 27.52 4COLT 27.00 4NE87615 25.69 4NE87619 31.26 4NE87627 23.23 4The .vrb fileThe .vrb file contains the estimates of the effects together with their approximateprediction variance matrix corresponding to the dense portion. The file isformatted for reading back for post processing. The number of equations in thedense portion can be increased (to a maximum of 800) using the !DENSE option(Table 5.5) but not to include random effects. The matrix is lower triangularrow-wise in the order that the parameters are printed in the .sln file. It can bethought of as a partitioned lower triangular matrix,⎡⎤⎣ σ2 .⎦˜β Dσ 2 C DD
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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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Page 178 and 179: 10 Tabulation of the data andpredic
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Page 192 and 193: 11 Functions of variancecomponentsI
Page 194 and 195: 11 Functions of variance components
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Page 198 and 199: 12 Command file: Running the jobInt
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Page 210 and 211: 13 Description of output filesIntro
Page 212 and 213: 13 Description of output files 190A
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Page 216 and 217: 13 Description of output files 194f
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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 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 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
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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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