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4 Data file preparation 44Fixed format data filesThe format must be supplied with the !FORMAT qualifier which is described in(Table 5.5). However, if all fields are present and are separated, the file can beread free format.Preparing data files in ExcelMany users find it convenient to prepare their data in Excel or Access. However,the data must be exported from these programs into either .csv (Commaseparated values) or .txt (TAB separated values) form for ASReml to read it.ASReml can convert an .xls file to a .csv file. When ASReml is invoked with an.xls file as the filename argument and there is no .csv file or .as with the samebasename, it exports the first sheet as a .csv file and then generates a template.as command file from any column headings it finds (see page 178). It will alsoconvert a Genstat .gsh spreadsheet file to .csv format. The data extracted fromthe .xls file are labels, numerical values and the results from formulae. Emptyrows at the start and end of a block are trimmed, but empty rows in the middleof a block are kept. Empty columns are ignored. A single row of labels as the firstnon-empty row in the block will be taken as column names. Empty cells in thisrow will have default names C1, C2 etc. assigned. Missing values are commonlyrepresented in ASReml data files by NA, * or .. ASReml will also recognise emptyfields as missing values in .csv (.xls) files.Binary format data filesConventions for binary files are as follows:• binary files are read as unformatted Fortran binary in single precision if thefilename has a .bin or .BIN extension,• Fortran binary data files are read in double precision if the filename has a .dblor .DBL extension,• ASReml recognises the value -1e37 as a missing value in binary files,• Fortran binary in the above means all real (.bin) or all double precision (.dbl)variables; mixed types, that is, integer and alphabetic binary representation ofvariables is not allowed in binary files,• binary files can only be used in conjunction with a pedigree file if the pedigreefields are coded in the binary file so that they correspond with the pedigree file(this can be done using the !SAVE option in ASReml to form the binary file,see Table 5.5), or the identifiers are whole numbers less than 9,999,999 and the!RECODE qualifier is specified (see Table 5.5).
5 Command file: Reading the dataIntroductionImportant rulesTitle lineSpecifying and reading the dataData field definition syntaxTransforming the dataTransformation syntaxOther rules and examplesSpecial note on covariatesOther examplesDatafile lineDatafile line syntaxDatafile qualifiersJob control qualifiers45
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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
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
Page 58 and 59: 3 A guided tour 36* SYNTAX change:
Page 60 and 61: 3 A guided tour 38repl 3 -0.8713 1.
Page 62 and 63: 3 A guided tour 40title linenin all
Page 64 and 65: 4 Data file preparation 424.1 Intro
Page 68 and 69: 5 Command file: Reading the data 46
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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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