Nothing
tests/testthat/test-seeduse-mipred.cv.R
In mipred: Prediction using Multiple Imputation
context("use of seed")
skip('seeduse tests mipred.cv')
cll <- readRDS("CLL_BMJ.rds")
cll_bin<-cll
cll_bin$srv5y_s[cll_bin$srv5y>12] <- 0 # Apply an administrative censorship at t=84 months
cll_bin$srv5y[cll_bin$srv5y>12] <- 12
cll_bin$Status[cll_bin$srv5y_s==1]<- 1 # Define the "Status" variable
cll_bin$Status[cll_bin$srv5y_s==0] <- 0 # Ss numeric -> 1:Dead, 0:Alive
cll_bin$Censor <- NULL
cll_bin$srv5y <- NULL
cll_bin$srv5y_s <- NULL
seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
8229, 7099)
output <- list(pred = structure(c(0.318476658047352, 0.278277048107985,
0.289117615852041, 0.211135171149873, 0.249522308432969, 0.389771192560319,
0.344979895206721, 0.216660595127165, 0.250288239652983, 0.269703726833673,
0.340352700823184, 0.338771774439977, 0.217077885020672, 0.342369169017627,
0.268697134810221, 0.278026334858864, 0.214169049820016, 0.215308412975576,
0.271178672807153, 0.266674919110185, 0.341249667738499, 0.215567971662233,
0.261426874822799, 0.350285378901966, 0.256780283310259, 0.344710099594545,
0.213446287452638, 0.253511703583354, 0.249119937145298, 0.227954602444087,
0.34707266046736, 0.382455456070599, 0.338149661021268, 0.213137076693493,
0.215204653018046, 0.259939748511985, 0.237919046938709, 0.330902467090568,
0.274713617631881, 0.364255856021758, 0.209961031699854, 0.206862493588199,
0.251859201242077, 0.259085776797963, 0.268234912149884, 0.367849258607926,
0.339525745521949, 0.258335788863199, 0.272627528567793, 0.389771192560319,
0.333901248262856, 0.341594958243188, 0.335405709883753, 0.207223225120957,
0.250847437064224, 0.450846610364685, 0.212519635387817, 0.263667844831566,
0.339767951772685, 0.218542971159667, 0.253976957062959, 0.255511417848828,
0.259013895750118, 0.364403702004156, 0.415594443312706, 0.278790858499278,
0.269784819819288, 0.208131361926957, 0.264254791434256, 0.201317614129306,
0.247686439738609, 0.378667030244566, 0.268455804092921, 0.253279288017807,
0.391608047501748, 0.278143940261787, 0.340628569161037, 0.338906170378138,
0.262795790658015, 0.276553228857715, 0.251945633251127, 0.33273702565185,
0.30674508188831, 0.25240898444152, 0.328467980666689, 0.211698413405678,
0.211749671706206, 0.267491854421763, 0.227954602444087, 0.25584359521477,
0.217182298207491, 0.274774815388889, 0.345751468307675, 0.370532544078995,
0.21733898601965, 0.197010229977143, 0.242402572755818, 0.274287406495075,
0.344571362758253, 0.264293421262534, 0.334594527617378, 0.27957784513664,
0.267672427515245, 0.208386092619483, 0.356399864612504, 0.274287406495075,
0.275325976079974, 0.279821738707483, 0.206668767939497, 0.335816599981964,
0.339870191649064, 0.263538862943414, 0.33424287599314, 0.270348735365247,
0.255376092823931, 0.327758176036003, 0.322726854491937, 0.270390287474222,
0.337806066294044, 0.310851231286767, 0.274160351736859, 0.212314112058644,
0.328608809086156, 0.340008017558864, 0.17539896042577, 0.285956156147657,
0.253362469340261, 0.331310590641769, 0.337188027181408, 0.375055287027818,
0.394216618067206, 0.317693182144981, 0.357138743661345, 0.211391054209229,
0.311689606998716, 0.38687034141343, 0.346592920954192, 0.366952565854258,
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0.335748101015052, 0.305106657868705, 0.263715622314504, 0.316804207297008,
0.353749388639698, 0.340008017558864, 0.280473791901386, 0.297111188723024,
0.301833519982424, 0.370532544078995, 0.248241781684749, 0.369645383307968,
0.215983737384082, 0.271603785352225, 0.263554125494824, 0.326060303359362,
0.406409587814761, 0.269482406771498, 0.337119390462037, 0.394427855656135,
0.207879908211654, 0.385041644674155, 0.251179208870145, 0.215152786650363,
0.210419905758043, 0.256721674595334, 0.265921108179742, 0.347977994890574,
0.344164144859683, 0.3361591983996, 0.210879515003454, 0.295369406219235,
0.257836736788262, 0.192074022040805, 0.252756868035715, 0.157226288152208,
0.315010057146063, 0.213394729636435, 0.217025692033945, 0.260194544867895,
0.256077556900082, 0.317512884674265, 0.311678329560489, 0.392527631099592,
0.343185454321166, 0.338218400476129, 0.213497854344633, 0.243947046402045,
0.21744348991454, 0.419347425780873, 0.25625312021214, 0.344432652410444,
0.295369406219235, 0.112178247829054, 0.212725303937648, 0.178242569199466,
0.284433303290058, 0.261313779005266, 0.278801427961955, 0.330183874078827,
0.338837362710635, 0.359947537352971, 0.248890205453823, 0.342369169017627,
0.334447936149812, 0.343094466446735, 0.22582160247482, 0.413721588194801,
0.265630466640554, 0.360836869521144, 0.247000329408915, 0.319187328745714,
0.217077885020672, 0.33335500640596, 0.302647161537581, 0.270753978314213,
0.215855977710551, 0.257895511741712, 0.254559315321942, 0.30933703001785,
0.333605854179501, 0.218647892242237, 0.360836869521144, 0.314178153060384,
0.213497854344633, 0.256663074637884, 0.318338113002256, 0.289911213346933,
0.217315306191547, 0.244098634409356, 0.251251664929358, 0.264075692516856,
0.338287146762276, 0.221176877149173, 0.286624778118167, 0.248603240103813,
0.268154333718955, 0.241501289765835, 0.367088661282974, 0.334649316185711,
0.272627528567793, 0.322678244424582, 0.262049026548806, 0.246088103294615,
0.397136874239036, 0.343106313990544, 0.311689606998716, 0.236141687080068,
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0.240406750709935, 0.328797889388855, 0.340766543855735, 0.203066698060366,
0.251772022058241, 0.229884959274666, 0.324227093749549, 0.30674508188831,
0.332672832991699, 0.236901734741315, 0.272698848953472, 0.328479575694349,
0.265054523928038, 0.417482523170427, 0.366192748576653, 0.392375418730081,
0.239702921149871, 0.339456876654057, 0.21401402242476, 0.412798833791985,
0.218280827146825, 0.256545900998611, 0.192074022040805, 0.332059476027492,
0.427825204406016, 0.256897527009326, 0.2109817502325, 0.255259304966803,
0.32873011349675, 0.35911579829215, 0.311815302017182, 0.217077885020672,
0.343808784137928, 0.312643801720051, 0.327758176036003, 0.248029973929245,
0.196439440818991, 0.245120120482969, 0.27501969107536, 0.234701025058472,
0.203315322846204, 0.270632713866559, 0.268071655398011, 0.215204653018046,
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0.346516080435515, 0.276676139830661, 0.219435956440444, 0.345126468848312,
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0.263543922836054, 0.360836869521144, 0.216504261100954, 0.246543632627378,
0.28899722813945, 0.278709033032818, 0.338906170378138, 0.252351034686709,
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0.256019053327452, 0.340697553133123, 0.335748101015052, 0.214531098038895,
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0.33554264558689, 0.33445241182978, 0.213085573332747, 0.343393170994405,
0.231253870113548, 0.256663074637884, 0.21401402242476, 0.409264279707781,
0.289911213346933, 0.117696977996457, 0.253315922220202, 0.212828192669884,
0.324238611355054, 0.341180629825638, 0.277419296951917, 0.273613507139854,
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"499", "500"), NULL)))
mice.options <- NULL
mice.options$seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:4]
mice.options$maxit <- 2
set.seed(12345)
test_that("output replicates from specified seed for mipred and averaging method",{
expect_equal(mipred.cv(Status~age10+cyto,family=binomial,data=cll_bin[1:500,-1], nimp=2, folds=2, mice.options=mice.options)[2:3],output)
})
output <- list(pred = structure(c(0.324626090711691, 0.238581567478475,
0.293592625651323, 0.215010760130649, 0.232880215770661, 0.47232338268786,
0.352656783713505, 0.214139162183645, 0.249097262126295, 0.273095090570347,
0.214383275849187, 0.39631812077668, 0.214074099369918, 0.349895510961235,
0.239962808080433, 0.250188503953077, 0.214529841143926, 0.369655343433018,
0.239601574703534, 0.331696120559728, 0.369553989161271, 0.214310020509734,
0.264364606535924, 0.388376763536027, 0.231802626489789, 0.368991119532943,
0.214643886717997, 0.232284955547446, 0.232940663804656, 0.229127992442298,
0.368608571626731, 0.392279505044733, 0.370060875386354, 0.214692776877661,
0.214366995311559, 0.26279659634823, 0.372836893841835, 0.215508804003521,
0.239091198065259, 0.368661537630019, 0.233113432668393, 0.181598759735883,
0.254280173045383, 0.231727229247033, 0.297747461922618, 0.339521596260721,
0.369835557181046, 0.294380359249285, 0.272443451547587, 0.400008928020172,
0.370759721211097, 0.369497686201993, 0.370511681545583, 0.215639576894638,
0.232681677726231, 0.496529529775724, 0.214790581469845, 0.266727830318417,
0.347144264514679, 0.238397230092369, 0.232216008563053, 0.258128616158334,
0.231475730281952, 0.373197945837601, 0.422681467838723, 0.278895258908529,
0.23980417194121, 0.22628683193719, 0.240615733029875, 0.201194820815077,
0.233156638817423, 0.383826480617341, 0.215329085213238, 0.232319434393133,
0.401949251997194, 0.282003367509617, 0.369655343433018, 0.369936943362472,
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2L), .Dimnames = list(c("1", "2", "3", "4", "5", "6", "7", "8",
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"485", "486", "487", "488", "489", "490", "491", "492", "493",
"494", "495", "496", "497", "498", "499", "500"), NULL)))
mice.options <- NULL
mice.options$seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:2]
mice.options$maxit <- 2
set.seed(12345)
test_that("output replicates from specified seed for mipred and rubin method",{
expect_equal(mipred.cv(Status~age10+cyto,family=binomial,data=cll_bin[1:500,-1], nimp=2, folds=2, mice.options=mice.options, method="rubin")[2:3],output)
})
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mipred documentation built on July 12, 2019, 5:04 p.m.
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context("use of seed")
skip('seeduse tests mipred.cv')
cll <- readRDS("CLL_BMJ.rds")
cll_bin<-cll
cll_bin$srv5y_s[cll_bin$srv5y>12] <- 0 # Apply an administrative censorship at t=84 months
cll_bin$srv5y[cll_bin$srv5y>12] <- 12
cll_bin$Status[cll_bin$srv5y_s==1]<- 1 # Define the "Status" variable
cll_bin$Status[cll_bin$srv5y_s==0] <- 0 # Ss numeric -> 1:Dead, 0:Alive
cll_bin$Censor <- NULL
cll_bin$srv5y <- NULL
cll_bin$srv5y_s <- NULL
seeds <- c(7350, 5880, 2571, 3887, 9745, 5608, 3468, 2711, 3448, 4676,
1627, 5087, 6479, 3901, 1037, 6622, 4832, 3382, 8515, 268, 3210,
5944, 3380, 3646, 9188, 2750, 7987, 466, 2981, 136, 5134, 8476,
5618, 8948, 1590, 5281, 2551, 2052, 1444, 8688, 1691, 6398, 4728,
8267, 5274, 4154, 982, 7540, 3081, 5286, 6405, 1238, 5589, 8221,
6026, 1922, 7651, 3100, 4341, 2134, 9685, 4524, 9750, 7618, 8211,
2438, 824, 6982, 6548, 9743, 4302, 9038, 185, 4418, 1306, 6643,
9865, 3436, 6151, 9647, 4261, 8109, 7573, 127, 571, 4545, 7245,
4764, 5038, 9037, 6085, 1459, 5124, 9463, 942, 2241, 6492, 3190,
8229, 7099)
output <- list(pred = structure(c(0.318476658047352, 0.278277048107985,
0.289117615852041, 0.211135171149873, 0.249522308432969, 0.389771192560319,
0.344979895206721, 0.216660595127165, 0.250288239652983, 0.269703726833673,
0.340352700823184, 0.338771774439977, 0.217077885020672, 0.342369169017627,
0.268697134810221, 0.278026334858864, 0.214169049820016, 0.215308412975576,
0.271178672807153, 0.266674919110185, 0.341249667738499, 0.215567971662233,
0.261426874822799, 0.350285378901966, 0.256780283310259, 0.344710099594545,
0.213446287452638, 0.253511703583354, 0.249119937145298, 0.227954602444087,
0.34707266046736, 0.382455456070599, 0.338149661021268, 0.213137076693493,
0.215204653018046, 0.259939748511985, 0.237919046938709, 0.330902467090568,
0.274713617631881, 0.364255856021758, 0.209961031699854, 0.206862493588199,
0.251859201242077, 0.259085776797963, 0.268234912149884, 0.367849258607926,
0.339525745521949, 0.258335788863199, 0.272627528567793, 0.389771192560319,
0.333901248262856, 0.341594958243188, 0.335405709883753, 0.207223225120957,
0.250847437064224, 0.450846610364685, 0.212519635387817, 0.263667844831566,
0.339767951772685, 0.218542971159667, 0.253976957062959, 0.255511417848828,
0.259013895750118, 0.364403702004156, 0.415594443312706, 0.278790858499278,
0.269784819819288, 0.208131361926957, 0.264254791434256, 0.201317614129306,
0.247686439738609, 0.378667030244566, 0.268455804092921, 0.253279288017807,
0.391608047501748, 0.278143940261787, 0.340628569161037, 0.338906170378138,
0.262795790658015, 0.276553228857715, 0.251945633251127, 0.33273702565185,
0.30674508188831, 0.25240898444152, 0.328467980666689, 0.211698413405678,
0.211749671706206, 0.267491854421763, 0.227954602444087, 0.25584359521477,
0.217182298207491, 0.274774815388889, 0.345751468307675, 0.370532544078995,
0.21733898601965, 0.197010229977143, 0.242402572755818, 0.274287406495075,
0.344571362758253, 0.264293421262534, 0.334594527617378, 0.27957784513664,
0.267672427515245, 0.208386092619483, 0.356399864612504, 0.274287406495075,
0.275325976079974, 0.279821738707483, 0.206668767939497, 0.335816599981964,
0.339870191649064, 0.263538862943414, 0.33424287599314, 0.270348735365247,
0.255376092823931, 0.327758176036003, 0.322726854491937, 0.270390287474222,
0.337806066294044, 0.310851231286767, 0.274160351736859, 0.212314112058644,
0.328608809086156, 0.340008017558864, 0.17539896042577, 0.285956156147657,
0.253362469340261, 0.331310590641769, 0.337188027181408, 0.375055287027818,
0.394216618067206, 0.317693182144981, 0.357138743661345, 0.211391054209229,
0.311689606998716, 0.38687034141343, 0.346592920954192, 0.366952565854258,
0.269482406771498, 0.343185454321166, 0.216504261100954, 0.219699097822628,
0.335748101015052, 0.305106657868705, 0.263715622314504, 0.316804207297008,
0.353749388639698, 0.340008017558864, 0.280473791901386, 0.297111188723024,
0.301833519982424, 0.370532544078995, 0.248241781684749, 0.369645383307968,
0.215983737384082, 0.271603785352225, 0.263554125494824, 0.326060303359362,
0.406409587814761, 0.269482406771498, 0.337119390462037, 0.394427855656135,
0.207879908211654, 0.385041644674155, 0.251179208870145, 0.215152786650363,
0.210419905758043, 0.256721674595334, 0.265921108179742, 0.347977994890574,
0.344164144859683, 0.3361591983996, 0.210879515003454, 0.295369406219235,
0.257836736788262, 0.192074022040805, 0.252756868035715, 0.157226288152208,
0.315010057146063, 0.213394729636435, 0.217025692033945, 0.260194544867895,
0.256077556900082, 0.317512884674265, 0.311678329560489, 0.392527631099592,
0.343185454321166, 0.338218400476129, 0.213497854344633, 0.243947046402045,
0.21744348991454, 0.419347425780873, 0.25625312021214, 0.344432652410444,
0.295369406219235, 0.112178247829054, 0.212725303937648, 0.178242569199466,
0.284433303290058, 0.261313779005266, 0.278801427961955, 0.330183874078827,
0.338837362710635, 0.359947537352971, 0.248890205453823, 0.342369169017627,
0.334447936149812, 0.343094466446735, 0.22582160247482, 0.413721588194801,
0.265630466640554, 0.360836869521144, 0.247000329408915, 0.319187328745714,
0.217077885020672, 0.33335500640596, 0.302647161537581, 0.270753978314213,
0.215855977710551, 0.257895511741712, 0.254559315321942, 0.30933703001785,
0.333605854179501, 0.218647892242237, 0.360836869521144, 0.314178153060384,
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0.240406750709935, 0.328797889388855, 0.340766543855735, 0.203066698060366,
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0.265054523928038, 0.417482523170427, 0.366192748576653, 0.392375418730081,
0.239702921149871, 0.339456876654057, 0.21401402242476, 0.412798833791985,
0.218280827146825, 0.256545900998611, 0.192074022040805, 0.332059476027492,
0.427825204406016, 0.256897527009326, 0.2109817502325, 0.255259304966803,
0.32873011349675, 0.35911579829215, 0.311815302017182, 0.217077885020672,
0.343808784137928, 0.312643801720051, 0.327758176036003, 0.248029973929245,
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-0.976091659905809, -0.933631119118252, -0.571044036119645, -1.28427120182172
), .Dim = c(500L, 2L), .Dimnames = list(c("1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15",
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26",
"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37",
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48",
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59",
"60", "61", "62", "63", "64", "65", "66", "67", "68", "69", "70",
"71", "72", "73", "74", "75", "76", "77", "78", "79", "80", "81",
"82", "83", "84", "85", "86", "87", "88", "89", "90", "91", "92",
"93", "94", "95", "96", "97", "98", "99", "100", "101", "102",
"103", "104", "105", "106", "107", "108", "109", "110", "111",
"112", "113", "114", "115", "116", "117", "118", "119", "120",
"121", "122", "123", "124", "125", "126", "127", "128", "129",
"130", "131", "132", "133", "134", "135", "136", "137", "138",
"139", "140", "141", "142", "143", "144", "145", "146", "147",
"148", "149", "150", "151", "152", "153", "154", "155", "156",
"157", "158", "159", "160", "161", "162", "163", "164", "165",
"166", "167", "168", "169", "170", "171", "172", "173", "174",
"175", "176", "177", "178", "179", "180", "181", "182", "183",
"184", "185", "186", "187", "188", "189", "190", "191", "192",
"193", "194", "195", "196", "197", "198", "199", "200", "201",
"202", "203", "204", "205", "206", "207", "208", "209", "210",
"211", "212", "213", "214", "215", "216", "217", "218", "219",
"220", "221", "222", "223", "224", "225", "226", "227", "228",
"229", "230", "231", "232", "233", "234", "235", "236", "237",
"238", "239", "240", "241", "242", "243", "244", "245", "246",
"247", "248", "249", "250", "251", "252", "253", "254", "255",
"256", "257", "258", "259", "260", "261", "262", "263", "264",
"265", "266", "267", "268", "269", "270", "271", "272", "273",
"274", "275", "276", "277", "278", "279", "280", "281", "282",
"283", "284", "285", "286", "287", "288", "289", "290", "291",
"292", "293", "294", "295", "296", "297", "298", "299", "300",
"301", "302", "303", "304", "305", "306", "307", "308", "309",
"310", "311", "312", "313", "314", "315", "316", "317", "318",
"319", "320", "321", "322", "323", "324", "325", "326", "327",
"328", "329", "330", "331", "332", "333", "334", "335", "336",
"337", "338", "339", "340", "341", "342", "343", "344", "345",
"346", "347", "348", "349", "350", "351", "352", "353", "354",
"355", "356", "357", "358", "359", "360", "361", "362", "363",
"364", "365", "366", "367", "368", "369", "370", "371", "372",
"373", "374", "375", "376", "377", "378", "379", "380", "381",
"382", "383", "384", "385", "386", "387", "388", "389", "390",
"391", "392", "393", "394", "395", "396", "397", "398", "399",
"400", "401", "402", "403", "404", "405", "406", "407", "408",
"409", "410", "411", "412", "413", "414", "415", "416", "417",
"418", "419", "420", "421", "422", "423", "424", "425", "426",
"427", "428", "429", "430", "431", "432", "433", "434", "435",
"436", "437", "438", "439", "440", "441", "442", "443", "444",
"445", "446", "447", "448", "449", "450", "451", "452", "453",
"454", "455", "456", "457", "458", "459", "460", "461", "462",
"463", "464", "465", "466", "467", "468", "469", "470", "471",
"472", "473", "474", "475", "476", "477", "478", "479", "480",
"481", "482", "483", "484", "485", "486", "487", "488", "489",
"490", "491", "492", "493", "494", "495", "496", "497", "498",
"499", "500"), NULL)))
mice.options <- NULL
mice.options$seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:4]
mice.options$maxit <- 2
set.seed(12345)
test_that("output replicates from specified seed for mipred and averaging method",{
expect_equal(mipred.cv(Status~age10+cyto,family=binomial,data=cll_bin[1:500,-1], nimp=2, folds=2, mice.options=mice.options)[2:3],output)
})
output <- list(pred = structure(c(0.324626090711691, 0.238581567478475,
0.293592625651323, 0.215010760130649, 0.232880215770661, 0.47232338268786,
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-0.855263083722481, -0.923927246257701, -1.00649506085083), .Dim = c(500L,
2L), .Dimnames = list(c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
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"97", "98", "99", "100", "101", "102", "103", "104", "105", "106",
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"224", "225", "226", "227", "228", "229", "230", "231", "232",
"233", "234", "235", "236", "237", "238", "239", "240", "241",
"242", "243", "244", "245", "246", "247", "248", "249", "250",
"251", "252", "253", "254", "255", "256", "257", "258", "259",
"260", "261", "262", "263", "264", "265", "266", "267", "268",
"269", "270", "271", "272", "273", "274", "275", "276", "277",
"278", "279", "280", "281", "282", "283", "284", "285", "286",
"287", "288", "289", "290", "291", "292", "293", "294", "295",
"296", "297", "298", "299", "300", "301", "302", "303", "304",
"305", "306", "307", "308", "309", "310", "311", "312", "313",
"314", "315", "316", "317", "318", "319", "320", "321", "322",
"323", "324", "325", "326", "327", "328", "329", "330", "331",
"332", "333", "334", "335", "336", "337", "338", "339", "340",
"341", "342", "343", "344", "345", "346", "347", "348", "349",
"350", "351", "352", "353", "354", "355", "356", "357", "358",
"359", "360", "361", "362", "363", "364", "365", "366", "367",
"368", "369", "370", "371", "372", "373", "374", "375", "376",
"377", "378", "379", "380", "381", "382", "383", "384", "385",
"386", "387", "388", "389", "390", "391", "392", "393", "394",
"395", "396", "397", "398", "399", "400", "401", "402", "403",
"404", "405", "406", "407", "408", "409", "410", "411", "412",
"413", "414", "415", "416", "417", "418", "419", "420", "421",
"422", "423", "424", "425", "426", "427", "428", "429", "430",
"431", "432", "433", "434", "435", "436", "437", "438", "439",
"440", "441", "442", "443", "444", "445", "446", "447", "448",
"449", "450", "451", "452", "453", "454", "455", "456", "457",
"458", "459", "460", "461", "462", "463", "464", "465", "466",
"467", "468", "469", "470", "471", "472", "473", "474", "475",
"476", "477", "478", "479", "480", "481", "482", "483", "484",
"485", "486", "487", "488", "489", "490", "491", "492", "493",
"494", "495", "496", "497", "498", "499", "500"), NULL)))
mice.options <- NULL
mice.options$seed <- as.vector(matrix(seeds,ncol=1,nrow=5*5))[1:2]
mice.options$maxit <- 2
set.seed(12345)
test_that("output replicates from specified seed for mipred and rubin method",{
expect_equal(mipred.cv(Status~age10+cyto,family=binomial,data=cll_bin[1:500,-1], nimp=2, folds=2, mice.options=mice.options, method="rubin")[2:3],output)
})
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