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13 Description of output files 202test is calculated directly from the residuals rather than from the analysis.They are intended to flag the records with large residuals rather than to preciselyquantify their relative size. They are not studentised residuals and aregenerally not relevant when the user has fitted heterogeneous variances.This is nin89a.res.Convergence sequence of variance parametersIteration 1 2 3 4 5 6LogL -401.827 -400.780 -399.807 -399.353 -399.326 -399.324Change % 59 80 83 21 5 1Adjusted 0 0 0 0 0 0StepSz 0.316 0.562 1.000 1.000 1.000 1.0005 0.500000 0.538787 0.589519 0.639457 0.651397 0.654445 0.56 0.500000 0.487564 0.469768 0.448895 0.440861 0.438406 -0.6Plot of Residuals [-24.8730 15.9145] vs Fitted values [ 16.7724 35.9355] RvE-----------------------------1------------------------------| 1 || 1 || 1 1 1 |1 3 11 112 1 1 21 1 1 1 |1 211 24 1311 112 1 || 1 1 411 111122 12 || 1 1 1 4 1 13 1131111132 2 1 2 |2 1 1 11 2 21221 11 1 2 1 || 1 2 1 21 2 1321 1 1 3 2 2 |------------1-1-------1-11-1-421122---3---------------------| 1 1 11 1 2 31111 12 1 |2 1 1 1 11 || 1 12 || 1 1 1 |1 1 1 1 || 11 1 || 21 1 11 || |1 11 || 1 || 1 || 1 || 111 1 |----------------------------1---1---1----1------------------SLOPES FOR LOG(ABS(RES)) on LOG(PV) for Section 10.15*** ** **** ** *** *** *** *** *** *********** ************************ * * * ** ******************* ** ** ** ** ***** ** ************************ ** *Min Mean Max -24.873 0.27954 15.915 omitting 18 zeros
13 Description of output files 203Spatial diagnostic statistics of Residuals 22 11Residual Plot and Autocorrelations [se 0.077]| ++xxx+X||--- - O+ + x +x+x>+X ||o - -- + +++xxx++X++||+ + + +x- +xxx+++|| o -- ++ +- xx+xHxx||-+xxx+xXx +++x xX ++x||-++ o- +XxxXXx-xXX +++||ooL
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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
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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
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Page 216 and 217: 13 Description of output files 194f
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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
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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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