Subject index - Stata

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38 Subject index fvwrapon, set subcommand, [R] set, [R] set showbaselevels [fweight=exp] modifier, [U] 11.1.6 weight, [U] 20.23.1 Frequency weights fwrite() function, [M-5] fopen( ) fwrite() function, [M-5] fopen( ) fxsize() option, [G-2] graph combine fysize() option, [G-2] graph combine G g2 inverse of matrix, [P] matrix define, [P] matrix svd gain, [TS] tsfilter, [TS] tsfilter bk, [TS] tsfilter bw, [TS] tsfilter cf, [TS] tsfilter hp, [TS] Glossary gamma density function, [D] functions incomplete, [D] functions distribution cumulative, [D] functions inverse cumulative, [D] functions inverse reverse cumulative, [D] functions reverse cumulative, [D] functions regression, [SEM] intro 5, [SEM] Glossary gamma option, see gsem option gamma gamma() function, [M-5] factorial( ) gammaden() function, [D] functions, [M-5] normal( ) gammap() function, [D] functions, [M-5] normal( ) gammaptail() function, [D] functions, [M-5] normal( ) gap() option, [G-2] graph twoway histogram gaps, [ST] stbase, [ST] stdescribe, [ST] stgen, [ST] stset, [ST] Glossary GARCH, see generalized autoregressive conditional heteroskedasticity Gauss–Hermite quadrature, see quadrature, Gauss– Hermite Gauss–Seidel method, [M-5] solvenl( ) Gauss, reading data from, [U] 21.4 Transfer programs Gaussian kernel function, [G-2] graph twoway kdensity, [G-2] graph twoway lpoly, [R] kdensity, [R] lpoly, [R] qreg, [TE] teffects overlap Gaussian regression, [SEM] Glossary GEE, see generalized estimating equations geigen la() function, [M-5] geigensystem( ) geigenselect* la() functions, [M-5] geigensystem( ) geigensystem() function, [M-5] geigensystem( ) geigensystem la() function, [M-5] geigensystem( ) geigensystemselect*() functions, [M-5] geigensystem( ) generalized autoregressive conditional heteroskedasticity, [TS] arch, [TS] Glossary eigensystem, [M-5] geigensystem( ) eigenvalues, [M-6] Glossary estimating equations, [XT] xtgee, [XT] Glossary gamma survival regression, [ST] streg generalized, continued Hessenberg decomposition, [M-5] ghessenbergd( ) inverse, [M-5] invsym( ), [M-5] pinv( ), [M-5] qrinv( ) inverse of matrix, [P] matrix define, [P] matrix svd least squares, estimated, see estimated generalized least squares feasible, see feasible generalized least squares least-squares estimator, [TS] prais, [TS] Glossary linear latent and mixed models, [R] gllamm linear mixed model, [ME] me, [ME] Glossary linear mixed-effects model, [ME] me, [ME] meglm, [ME] Glossary linear models, [R] binreg, [R] glm, [SVY] svy estimation, [U] 26.6 Generalized linear models, [U] 26.18.3 Generalized linear models with panel data, [XT] xtgee, [XT] Glossary linear response functions, [SEM] Glossary method of moments, [P] matrix accum, [SEM] Glossary, [U] 26.22 Generalized method of moments (GMM), [XT] xtabond, [XT] xtdpd, [XT] xtdpdsys, see gmm command negative binomial regression, [R] nbreg, [SVY] svy estimation response variables, [SEM] intro 2, [SEM] intro 5, [SEM] gsem family-and-link options responses, combined, [SEM] example 34g Schur decomposition, [M-5] gschurd( ) SEM, [SEM] Glossary generate, cluster subcommand, [MV] cluster generate icd9 subcommand, [D] icd9 icd9p subcommand, [D] icd9 sts subcommand, [ST] sts generate generate command, [D] generate, [MI] mi passive, [MI] mi xeq generate functions, adding, [MV] cluster programming subroutines generating data, [D] egen, [D] generate generating variables, [ST] stgen, [ST] sts generate get, constraint subcommand, [R] constraint net subcommand, [R] net get() function, [D] functions, [P] matrix define, [P] matrix get getmata command, [D] putmata getting started, [U] 1 Read this — it will help Getting Started with Stata manuals, [U] 1.1 Getting Started with Stata keyword search of, [U] 4 Stata’s help and search facilities gettoken command, [P] gettoken Geweke–Hajivassiliou–Keane multivariate normal simulator, [M-5] ghk( ), [M-5] ghkfast( ) ggof, estat subcommand, [SEM] estat ggof ghalton() function, [M-5] halton( ) ghessenbergd() function, [M-5] ghessenbergd( ) ghessenbergd() function, [M-5] ghessenbergd( )
Subject index 39 ghessenbergd la() function, [M-5] ghessenbergd( ) ghk() function, [M-5] ghk( ) ghkfast() function, [M-5] ghkfast( ) ghkfast i() function, [M-5] ghkfast( ) ghkfast init() function, [M-5] ghkfast( ) ghkfast init *() function, [M-5] ghkfast( ) ghkfast query *() function, [M-5] ghkfast( ) ghk init() function, [M-5] ghk( ) ghk init *() function, [M-5] ghk( ) ghk query npts() function, [M-5] ghk( ) GHQ, see quadrature, Gauss–Hermite ginvariant, estat subcommand, [SEM] estat ginvariant ginvariant() option, see sem option ginvariant() GJR, see threshold autoregressive conditional heteroskedasticity gladder command, [R] ladder GLLAMM, see generalized linear latent and mixed models gllamm command, [R] gllamm GLM, see generalized linear models glm command, [R] glm, [R] glm postestimation GLME, see generalized linear mixed-effects model GLMM, see generalized linear mixed model global command, [P] macro, [U] 18.3.2 Global macros, [U] 18.3.10 Advanced global macro manipulation global variable, [M-2] declarations, [M-5] direxternal( ), [M-5] findexternal( ), [M-5] valofexternal( ), [M-6] Glossary Global, class prefix operator, [P] class glogit command, [R] glogit, [R] glogit postestimation glsaccum, matrix subcommand, [P] matrix accum GMM, see generalized method of moments gmm command, [R] gmm, [R] gmm postestimation gnbreg command, [R] nbreg, [R] nbreg postestimation gof, estat subcommand, [R] estat gof, [R] poisson postestimation, [SEM] estat gof, [SVY] estat Gompertz survival regression, [ST] streg Gönen and Heller’s K, [ST] stcox postestimation Goodman and Kruskal’s gamma, [R] tabulate twoway goodness of fit, [R] brier, [R] diagnostic plots, [R] estat gof, [R] ksmirnov, [R] linktest, [R] logistic postestimation, [R] lrtest, [R] poisson postestimation, [R] regress postestimation, [SEM] intro 7, [SEM] estat eqgof, [SEM] estat ggof, [SEM] estat gof, [SEM] example 3, [SEM] example 4, [SEM] Glossary, [SVY] estat, also see deviance residual, also see normal distribution and normality, test for goto, [M-2] goto Gower coefficient similarity measure, [MV] measure option .gph file, [U] 11.6 Filenaming conventions gph files, [G-2] graph manipulation, [G-4] concept: gph files describing contents, [G-2] graph describe gprobit command, [R] glogit, [R] glogit postestimation gradient option, [R] maximize grammar, [M-2] syntax Granger causality, [TS] vargranger, [TS] Glossary graph bar command, [G-2] graph bar box command, [G-2] graph box combine command, [G-2] graph combine command, [G-2] graph copy command, [G-2] graph copy describe, [G-2] graph describe dir command, [G-2] graph dir display command, [G-2] graph display dot command, [G-2] graph dot, [G-3] area options, [G-3] line options drop command, [G-2] graph drop export command, [G-2] graph export hbar command, [G-2] graph bar hbox command, [G-2] graph box matrix command, [G-2] graph matrix pie command, [G-2] graph pie play command, [G-2] graph play print command, [G-2] graph print, [G-3] pr options query command, [G-2] graph query rename command, [G-2] graph rename save command, [G-2] graph save set command, [G-2] graph set set print command, [G-2] graph set twoway area command, [G-2] graph twoway area twoway bar command, [G-2] graph twoway bar twoway command, [G-2] graph twoway twoway connected command, [G-2] graph twoway connected twoway contour command, [G-2] graph twoway contour twoway contourline command, [G-2] graph twoway contourline twoway dot command, [G-2] graph twoway dot twoway dropline command, [G-2] graph twoway dropline twoway fpfit command, [G-2] graph twoway fpfit twoway fpfitci command, [G-2] graph twoway fpfitci twoway function command, [G-2] graph twoway function twoway histogram command, [G-2] graph twoway histogram twoway kdensity command, [G-2] graph twoway kdensity twoway lfit command, [G-2] graph twoway lfit twoway lfitci command, [G-2] graph twoway lfitci
Page 1 and 2: Subject index Symbols ! (not), see
Page 3 and 4: Subject index 3 alternative, contin
Page 5 and 6: Subject index 5 autoregressive, con
Page 7 and 8: Subject index 7 biquartimax rotatio
Page 9 and 10: Subject index 9 c(maxstrvarlen) c-c
Page 11 and 12: Subject index 11 char, continued ma
Page 13 and 14: Subject index 13 cluster analysis,
Page 15 and 16: Subject index 15 colnames, matrix s
Page 17 and 18: Subject index 17 confidence interva
Page 19 and 20: Subject index 19 convergence, [SEM]
Page 21 and 22: Subject index 21 cross-sectional da
Page 23 and 24: Subject index 23 defective matrix,
Page 25 and 26: Subject index 25 direction of an ef
Page 27 and 28: Subject index 27 dsign() function,
Page 29 and 30: Subject index 29 endogenous, contin
Page 31 and 32: Subject index 31 estat, continued m
Page 33 and 34: Subject index 33 experimental data,
Page 35 and 36: Subject index 35 files, continued c
Page 37: Subject index 37 frequencies, creat
Page 41 and 42: Subject index 41 graphs, continued
Page 43 and 44: Subject index 43 gsem option, conti
Page 45 and 46: Subject index 45 httpproxy, set sub
Page 47 and 48: Subject index 47 incidence-rate rat
Page 49 and 50: Subject index 49 invpoissontail() f
Page 51 and 52: Subject index 51 label values, [P]
Page 53 and 54: Subject index 53 lines, continued l
Page 55 and 56: Subject index 55 lower-triangular m
Page 57 and 58: Subject index 57 matmissing() funct
Page 59 and 60: Subject index 59 means, continued g
Page 61 and 62: Subject index 61 mindices, estat su
Page 63 and 64: Subject index 63 mreldifre() functi
Page 65 and 66: Subject index 65 nbinomialtail() fu
Page 67 and 68: Subject index 67 nonparametric anal
Page 69 and 70: Subject index 69 ocloglog option, s
Page 71 and 72: Subject index 71 outcomes, continue
Page 73 and 74: Subject index 73 pcorr command, [R]
Page 75 and 76: Subject index 75 postestimation com
Page 77 and 78: Subject index 77 probability of a t
Page 79 and 80: Subject index 79 quad precision, [M
Page 81 and 82: Subject index 81 rcap, graph twoway
Page 83 and 84: Subject index 83 reset, mi subcomma
Page 85 and 86: Subject index 85 robust, Huber/Whit
Page 87 and 88: Subject index 87 sample size, conti
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Subject index 89 sem command, [SEM]
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Subject index 91 set, cluster subco
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Subject index 93 snapshot, [D] snap
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Subject index 95 stability, [TS] va
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Subject index 97 stbase command, [S
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Subject index 99 Student’s t, dis
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Subject index 101 svy: mean command
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Subject index 103 tempfile command,
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Subject index 105 timer, continued
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Subject index 107 Tukey’s Student
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Subject index 109 use command, [D]
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Subject index 111 verifying data, [
Page 113 and 114:
Subject index 113 xtcloglog command
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Subject index - Stata

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