tests/testthat/dump_forward_selection.R
In mcol/nestfs: Cross-Validated (Nested) Forward Selection
fs.gauss.ok <-
structure(list(fs = structure(list(vars = c("age", "sex", "ltg",
"bmi", "map"), fdr = c(NA, NA, 1.096328429058e-06, 0.000756204135227493,
0.008709354629803), llks = c(NA, -2137.90427839746, -2060.04518471976,
-2010.23422271799, -1999.89688885129), diffs = c(NA, NA, 77.8590936777023,
49.810962001769, 10.3373338666966), iter = c(NA, NA, 1L, 2L,
3L)), class = "data.frame", row.names = c(NA, -5L)), init = c("age",
"sex"), panel = c("ltg", "bmi", "map"), init.model = "age + sex",
final.model = "age + sex + ltg + bmi + map", family = "gaussian",
params = list(test = "t", sel.crit = "paired.test", num.filter = 0,
filter.ignore = NULL, num.inner.folds = 10, max.iters = 3,
max.pval = 0.5, min.llk.diff = 2, seed = 50), iter1 = structure(list(
median.diff.llk = c(7.42822335017712, 4.3839536677425,
0.458637482580357, 0.315516355313903, 3.61710365564878,
3.50945113825658, 8.26341734691495), total.diff.llk = c(86.6091204903303,
41.4496088077674, 5.37230654548856, 2.34353871842285,
40.1920702138921, 41.7940561917314, 77.8590936777024),
p.value = c(4.78648489900619e-05, 6.79070902532288e-05,
0.0993854168436268, 0.271480574481681, 0.00145786039520934,
0.00309761355728272, 1.096328429058e-06)), class = "data.frame", row.names = c("bmi",
"map", "tc", "ldl", "hdl", "tch", "ltg")), all.iter = list(
structure(c(-218.235962780533, -209.412495468933, -215.584514536684,
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-218.388767255999, -219.018151956748, -220.252261154416,
-212.995447344712, -215.656289682965), .Dim = c(8L, 10L
), .Dimnames = list(c("Base", "bmi", "map", "tc", "ldl",
"hdl", "tch", "ltg"), NULL)), structure(c(-209.26295424083,
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-216.667342888255, -215.269697823286, -213.437658734681
), .Dim = c(7L, 10L), .Dimnames = list(c("Base", "bmi",
"map", "tc", "ldl", "hdl", "tch"), NULL)), structure(c(-204.750427386637,
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-202.249029293866, -202.931751727091, -205.55694128473,
-204.475195393701, -208.319333409614, -207.087069665534,
-206.547059297912, -205.024502952159), .Dim = c(6L, 10L
), .Dimnames = list(c("Base", "map", "tc", "ldl", "hdl",
"tch"), NULL)))), class = "fs")
fs.binom.ok <-
structure(list(fs = structure(list(vars = c("age", "sex", "ltg",
"bmi", "map"), fdr = c(NA, NA, 0.000123905514317849, 0.00224315781077807,
0.0238693735838184), llks = c(NA, -304.0483610766, -252.029036337961,
-231.971005782555, -226.180906570332), diffs = c(NA, NA, 52.0193247386388,
20.0580305554063, 5.79009921222334), iter = c(NA, NA, 1L, 2L,
3L)), class = "data.frame", row.names = c(NA, -5L)), init = c("age",
"sex"), panel = c("ltg", "bmi", "map"), init.model = "age + sex",
final.model = "age + sex + ltg + bmi + map", family = "binomial",
params = list(test = "t", sel.crit = "paired.test", num.filter = 0,
filter.ignore = NULL, num.inner.folds = 10, max.iters = 3,
max.pval = 0.5, min.llk.diff = 2, seed = 50), iter1 = structure(list(
median.diff.llk = c(4.38111229398526, 2.11556838718411,
0.138226177273646, -0.0123531319750096, 2.99745552926077,
3.15501415905757, 5.93880201665371), total.diff.llk = c(47.64415825756,
27.5539759797047, 2.05158848748997, 0.646902620696384,
32.8344571911067, 29.6468949551419, 52.0193247386388),
p.value = c(0.000214962121285572, 0.000443585799522373,
0.244793412686541, 0.412187247160204, 0.00252202165965489,
0.00260733432016639, 0.000123905514317849)), class = "data.frame", row.names = c("bmi",
"map", "tc", "ldl", "hdl", "tch", "ltg")), all.iter = list(
structure(c(-31.5525682431845, -27.0106110708928, -29.9078824684372,
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-28.8378708561204, -24.3030118593354, -30.0550494113573,
-27.2883120021651, -29.0734453251132, -30.2924634547718,
-30.4856143419512, -29.4144803807434, -29.1828459630946,
-25.7812368937484, -30.9533359307093, -24.5274249880595,
-29.5054964223396, -30.7991377875548, -30.6649066267911,
-24.6526458010058, -25.156582874197, -25.3024108156906,
-30.7181420011762, -26.4978745854974, -29.2702838591841,
-29.3465349113141, -29.4796957020986, -31.0687871879729,
-27.2194364740435, -30.3276992032938), .Dim = c(8L, 10L
), .Dimnames = list(c("Base", "bmi", "map", "tc", "ldl",
"hdl", "tch", "ltg"), NULL)), structure(c(-24.8390200872023,
-23.5541734274842, -23.5911143970304, -23.9814046910751,
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-31.4920518589283, -29.9939222390473, -29.2219992795914
), .Dim = c(7L, 10L), .Dimnames = list(c("Base", "bmi",
"map", "tc", "ldl", "hdl", "tch"), NULL)), structure(c(-23.5541734274842,
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), .Dimnames = list(c("Base", "map", "tc", "ldl", "hdl",
"tch"), NULL)))), class = "fs")
mcol/nestfs documentation built on Jan. 4, 2023, 12:38 p.m.
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fs.gauss.ok <-
structure(list(fs = structure(list(vars = c("age", "sex", "ltg",
"bmi", "map"), fdr = c(NA, NA, 1.096328429058e-06, 0.000756204135227493,
0.008709354629803), llks = c(NA, -2137.90427839746, -2060.04518471976,
-2010.23422271799, -1999.89688885129), diffs = c(NA, NA, 77.8590936777023,
49.810962001769, 10.3373338666966), iter = c(NA, NA, 1L, 2L,
3L)), class = "data.frame", row.names = c(NA, -5L)), init = c("age",
"sex"), panel = c("ltg", "bmi", "map"), init.model = "age + sex",
final.model = "age + sex + ltg + bmi + map", family = "gaussian",
params = list(test = "t", sel.crit = "paired.test", num.filter = 0,
filter.ignore = NULL, num.inner.folds = 10, max.iters = 3,
max.pval = 0.5, min.llk.diff = 2, seed = 50), iter1 = structure(list(
median.diff.llk = c(7.42822335017712, 4.3839536677425,
0.458637482580357, 0.315516355313903, 3.61710365564878,
3.50945113825658, 8.26341734691495), total.diff.llk = c(86.6091204903303,
41.4496088077674, 5.37230654548856, 2.34353871842285,
40.1920702138921, 41.7940561917314, 77.8590936777024),
p.value = c(4.78648489900619e-05, 6.79070902532288e-05,
0.0993854168436268, 0.271480574481681, 0.00145786039520934,
0.00309761355728272, 1.096328429058e-06)), class = "data.frame", row.names = c("bmi",
"map", "tc", "ldl", "hdl", "tch", "ltg")), all.iter = list(
structure(c(-218.235962780533, -209.412495468933, -215.584514536684,
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-212.995447344712, -215.656289682965), .Dim = c(8L, 10L
), .Dimnames = list(c("Base", "bmi", "map", "tc", "ldl",
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-205.55694128473, -212.326780992366, -218.60410300418,
-216.667342888255, -215.269697823286, -213.437658734681
), .Dim = c(7L, 10L), .Dimnames = list(c("Base", "bmi",
"map", "tc", "ldl", "hdl", "tch"), NULL)), structure(c(-204.750427386637,
-203.713950492143, -202.958657991477, -204.045864655351,
-204.511978711707, -205.777446985004, -212.59510841215,
-210.248746164587, -215.073181222047, -213.749412228182,
-213.849293605813, -212.688611406504, -198.847627209503,
-195.613319463586, -197.494467743798, -198.37899869796,
-197.130557098555, -198.709096606202, -199.839663947848,
-199.15931759368, -199.506229944442, -199.618265663703,
-199.802691794736, -200.627144532746, -195.755441235762,
-194.308596757446, -194.731338695782, -195.615079905159,
-193.517866090171, -195.299430366895, -199.53393017391,
-198.914153897268, -198.963910206497, -199.52201232213,
-197.704701442002, -199.17822751853, -192.894472456262,
-192.298588974501, -191.757074165081, -192.645718762211,
-192.027706626391, -193.108311328487, -197.445885830915,
-197.398781958025, -196.573091449743, -197.149114621446,
-196.901677282482, -197.326784125967, -203.014724780272,
-203.766238156356, -202.192779238686, -202.686756066292,
-202.249029293866, -202.931751727091, -205.55694128473,
-204.475195393701, -208.319333409614, -207.087069665534,
-206.547059297912, -205.024502952159), .Dim = c(6L, 10L
), .Dimnames = list(c("Base", "map", "tc", "ldl", "hdl",
"tch"), NULL)))), class = "fs")
fs.binom.ok <-
structure(list(fs = structure(list(vars = c("age", "sex", "ltg",
"bmi", "map"), fdr = c(NA, NA, 0.000123905514317849, 0.00224315781077807,
0.0238693735838184), llks = c(NA, -304.0483610766, -252.029036337961,
-231.971005782555, -226.180906570332), diffs = c(NA, NA, 52.0193247386388,
20.0580305554063, 5.79009921222334), iter = c(NA, NA, 1L, 2L,
3L)), class = "data.frame", row.names = c(NA, -5L)), init = c("age",
"sex"), panel = c("ltg", "bmi", "map"), init.model = "age + sex",
final.model = "age + sex + ltg + bmi + map", family = "binomial",
params = list(test = "t", sel.crit = "paired.test", num.filter = 0,
filter.ignore = NULL, num.inner.folds = 10, max.iters = 3,
max.pval = 0.5, min.llk.diff = 2, seed = 50), iter1 = structure(list(
median.diff.llk = c(4.38111229398526, 2.11556838718411,
0.138226177273646, -0.0123531319750096, 2.99745552926077,
3.15501415905757, 5.93880201665371), total.diff.llk = c(47.64415825756,
27.5539759797047, 2.05158848748997, 0.646902620696384,
32.8344571911067, 29.6468949551419, 52.0193247386388),
p.value = c(0.000214962121285572, 0.000443585799522373,
0.244793412686541, 0.412187247160204, 0.00252202165965489,
0.00260733432016639, 0.000123905514317849)), class = "data.frame", row.names = c("bmi",
"map", "tc", "ldl", "hdl", "tch", "ltg")), all.iter = list(
structure(c(-31.5525682431845, -27.0106110708928, -29.9078824684372,
-31.4303140317917, -31.8505552582312, -28.984590161543,
-30.6469603742333, -24.8390200872023, -30.3912317926556,
-24.9345266176307, -26.9407682587496, -28.7035027549902,
-29.0250090659235, -29.2162193235999, -25.5743807724468,
-24.1645528743669, -29.1965048442736, -28.7175608740323,
-24.8088562304427, -30.5326948408712, -30.751466188712,
-28.0400294485385, -30.3812757808314, -27.2965970954359,
-28.9826291362248, -26.6264800899483, -28.1143261559773,
-29.5308111162418, -29.526967456485, -25.5556961593448,
-27.6350629939131, -26.3890904242263, -30.9752812048587,
-20.3837479144357, -25.0392126510427, -30.3689233188759,
-30.245743974841, -22.5124305972306, -23.6913306946537,
-21.9996205972812, -29.3944553071312, -25.2966890282641,
-26.8080043075102, -29.7347557420656, -29.8156173869379,
-23.7452291074859, -26.0757193379246, -21.6257964873806,
-31.8291632050289, -25.1209756481142, -27.0261094180989,
-31.257634630633, -31.5558824539323, -28.0237957180286,
-28.8378708561204, -24.3030118593354, -30.0550494113573,
-27.2883120021651, -29.0734453251132, -30.2924634547718,
-30.4856143419512, -29.4144803807434, -29.1828459630946,
-25.7812368937484, -30.9533359307093, -24.5274249880595,
-29.5054964223396, -30.7991377875548, -30.6649066267911,
-24.6526458010058, -25.156582874197, -25.3024108156906,
-30.7181420011762, -26.4978745854974, -29.2702838591841,
-29.3465349113141, -29.4796957020986, -31.0687871879729,
-27.2194364740435, -30.3276992032938), .Dim = c(8L, 10L
), .Dimnames = list(c("Base", "bmi", "map", "tc", "ldl",
"hdl", "tch", "ltg"), NULL)), structure(c(-24.8390200872023,
-23.5541734274842, -23.5911143970304, -23.9814046910751,
-24.6757768730413, -24.5977165469897, -25.8094773308118,
-24.1645528743669, -22.1082694361047, -22.6586697320054,
-27.0620344682729, -25.3482576054173, -25.0189513986566,
-23.5110796617579, -27.2965970954359, -27.2660775173946,
-24.4657715290541, -25.9590709364872, -27.1467923098819,
-25.4659467615813, -27.2852741697325, -26.3890904242263,
-26.1420460006407, -26.7586656692688, -25.8130717732765,
-26.3503788877739, -23.540212675301, -25.8148209268978,
-21.9996205972812, -16.5778894834149, -19.0502755065157,
-21.0725136796833, -21.964451236062, -18.3049664630007,
-21.0408898526212, -21.6257964873806, -20.9371112078302,
-21.6407221896656, -20.2912420902586, -21.4644530775546,
-19.6698734255481, -22.0672238025557, -24.3030118593354,
-21.111796394476, -22.4042912306074, -23.2176691058786,
-24.155286526197, -23.620014024483, -24.969575342474,
-25.7812368937484, -24.6629636358891, -25.7114474039691,
-24.9899089167654, -25.630682517357, -26.2575893002672,
-26.10342445861, -25.3024108156906, -22.78529733673,
-25.1879792901851, -25.1755471292609, -25.4068281923898,
-23.2647786494067, -24.3291524456318, -30.3276992032938,
-26.8253813425906, -28.9582619775036, -32.6958933007038,
-31.4920518589283, -29.9939222390473, -29.2219992795914
), .Dim = c(7L, 10L), .Dimnames = list(c("Base", "bmi",
"map", "tc", "ldl", "hdl", "tch"), NULL)), structure(c(-23.5541734274842,
-22.9984743602015, -22.6789946793774, -23.0908705427532,
-23.5225358370309, -24.0378839728774, -22.1082694361047,
-20.8787237365477, -24.9357442412041, -23.780503360133,
-22.9505794762881, -21.8909672831465, -27.2660775173946,
-25.084548232339, -25.6800611467142, -26.5893403717929,
-26.2384670608921, -27.451266502175, -26.1420460006407,
-26.3599736919342, -25.5313268796485, -26.1752778877401,
-23.9422167472553, -25.8062234287072, -16.5778894834149,
-15.2943546673531, -15.5793376349046, -16.3139736745942,
-14.833249835246, -16.4037288800668, -20.9371112078302,
-21.3265565090565, -19.2736689875196, -20.3479455317682,
-19.2098457679436, -21.0568217768764, -21.111796394476,
-20.3260696641826, -19.8429461493815, -20.6654736726259,
-20.5616417698273, -21.4113321579357, -24.6629636358891,
-24.5534585105298, -23.6306696310505, -24.159756261869,
-25.0119357688556, -24.7593460330002, -22.78529733673,
-22.7501584130313, -22.8657500254987, -23.0169605366257,
-21.7119032419025, -22.4539576925348, -26.8253813425906,
-26.6085887851562, -28.6474965109508, -27.8750242673851,
-27.3464741952463, -26.5228469863968), .Dim = c(6L, 10L
), .Dimnames = list(c("Base", "map", "tc", "ldl", "hdl",
"tch"), NULL)))), class = "fs")
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