This function is primarily used as an internal function in jab_lmJaB.
Arguments
- mod
An
lmobject. Output from lmstats.- func.name
A character string of the function name used to calculate the desired centrality statistic.
- package.name
A character string of the name of the package that
func.namefunction is in. If left asNULLif the function will be called as loaded in the users environment.- args
A named list of additional arguments the
func.namefunction may need beyond themodobject.
Examples
library(stats)
data("LifeCycleSavings")
mod <- lm(sr ~ ., data = LifeCycleSavings)
# defined functions in stats
get_infl(mod, "dffits")
#> Australia Austria Belgium Bolivia Brazil
#> 0.06271756 0.06324405 0.18780542 -0.05967770 0.26464755
#> Canada Chile China Colombia Costa Rica
#> -0.03897262 -0.45535788 0.20077524 -0.09602160 0.40493458
#> Denmark Ecuador Finland France Germany
#> 0.38451126 -0.16946909 -0.14641688 0.27653834 -0.01521770
#> Greece Guatamala Honduras Iceland India
#> -0.28114772 -0.23053977 0.04816829 -0.47676403 0.03808618
#> Ireland Italy Japan Korea Luxembourg
#> 0.52157524 0.13884474 0.85965081 -0.43025048 -0.14006342
#> Malta Norway Netherlands New Zealand Nicaragua
#> 0.23855360 -0.05216187 0.03663477 0.14694487 0.03972980
#> Panama Paraguay Peru Philippines Portugal
#> -0.17751461 -0.46547654 0.48109398 0.48840149 -0.06901872
#> South Africa South Rhodesia Spain Sweden Switzerland
#> 0.03429664 0.16071740 -0.05261883 -0.45256252 0.19034296
#> Turkey Tunisia United Kingdom United States Venezuela
#> -0.14453378 -0.21765669 -0.27221843 -0.25095085 0.30708996
#> Zambia Jamaica Uruguay Libya Malaysia
#> 0.74823509 -0.34555773 -0.20513659 -1.16013341 -0.21262745
get_infl(mod, "rstudent")
#> Australia Austria Belgium Bolivia Brazil
#> 0.23271611 0.17095506 0.60655220 -0.19037831 0.96790816
#> Canada Chile China Colombia Costa Rica
#> -0.08983197 -2.31342946 0.69048169 -0.38946778 1.41731062
#> Denmark Ecuador Finland France Germany
#> 1.48644473 -0.64957871 -0.45986445 0.69640933 -0.04918692
#> Greece Guatamala Honduras Iceland India
#> -0.85967533 -0.90854545 0.19051919 -1.73119989 0.13729730
#> Ireland Italy Japan Korea Luxembourg
#> 1.00485886 0.52015744 1.60321582 -1.69103214 -0.45560591
#> Malta Norway Netherlands New Zealand Nicaragua
#> 0.81227407 -0.23247367 0.11605663 0.61373189 0.17254242
#> Panama Paraguay Peru Philippines Portugal
#> -0.88147653 -1.70488128 1.82391409 1.86382587 -0.21040432
#> South Africa South Rhodesia Spain Sweden Switzerland
#> 0.12996586 0.36714512 -0.18175853 -1.20293404 0.67532922
#> Turkey Tunisia United Kingdom United States Venezuela
#> -0.71138840 -0.76677907 -0.74959873 -0.35461507 0.99932569
#> Zambia Jamaica Uruguay Libya Malaysia
#> 2.85355834 -0.85376418 -0.62253411 -1.08930326 -0.80489153
# define the likelihood distance as influence statistic (Cook, 1986)
infl_like <- function(mod){
n <- length(mod$fitted.values)
p <- length(mod$coefficients)
ti <- rstudent(mod)
h <- hatvalues(mod)
p1 <- log( (n/(n-1)) * ((n-p-1) / (ti^2 +n-p-1)) )
p2 <- ti^2 * (n-1) / (1-h) / (n-p-1)
return(n*p1 + p2 - 1)
}
infl_like(mod)
#> Australia Austria Belgium Bolivia Brazil
#> 0.01332285 0.01393650 0.04279099 0.01329473 0.07801597
#> Canada Chile China Colombia Costa Rica
#> 0.01164427 0.46179324 0.04710546 0.01725230 0.19766003
#> Denmark Ecuador Finland France Germany
#> 0.18557686 0.03481345 0.02977880 0.08729178 0.01033835
#> Greece Guatamala Honduras Iceland India
#> 0.08834026 0.05925346 0.01191127 0.30613332 0.01132692
#> Ireland Italy Japan Korea Luxembourg
#> 0.30310916 0.02639617 0.85682344 0.25252760 0.02781943
#> Malta Norway Netherlands New Zealand Nicaragua
#> 0.06408061 0.01197483 0.01132621 0.02744299 0.01122802
#> Panama Paraguay Peru Philippines Portugal
#> 0.03527406 0.28988377 0.32837082 0.34491328 0.01445942
#> South Africa South Rhodesia Spain Sweden Switzerland
#> 0.01106509 0.03607130 0.01248200 0.23179598 0.04278521
#> Turkey Tunisia United Kingdom United States Venezuela
#> 0.02517964 0.05395529 0.08393131 0.07761392 0.10514619
#> Zambia Jamaica Uruguay Libya Malaysia
#> 1.21190479 0.13333477 0.05011857 1.49988249 0.05112667
get_infl(mod, "infl_like")
#> Error in infl_like(structure(list(coefficients = c(`(Intercept)` = 28.5660865407468, pop15 = -0.461193147122768, pop75 = -1.69149767674954, dpi = -0.000336901869141349, ddpi = 0.409694927870671), residuals = c(Australia = 0.863579763089957, Austria = 0.616385987736311, Belgium = 2.218957928338, Bolivia = -0.698319121223192, Brazil = 3.55280944158801, Canada = -0.316892362577826, Chile = -8.2422306716793, China = 2.53603608513497, Colombia = -1.45170709733013, `Costa Rica` = 5.1250781784526, Denmark = 5.40023884278033, Ecuador = -2.40563130331345, Finland = -1.68108565185996, France = 2.47547182883964, Germany = -0.180699295374666, Greece = -3.11616846782401, Guatamala = -3.35528378971092, Honduras = 0.710024484173062, Iceland = -6.21058197743013, India = 0.508673999894876, Ireland = 3.39113064057356, Italy = 1.92675489523614, Japan = 5.28148554984659, Korea = -6.10698144474573, Luxembourg = -1.67080656669553, Malta = 2.97490978233697, Norway = -0.871785361021597, Netherlands = 0.425545510217781, `New Zealand` = 2.28555481755543, Nicaragua = 0.646396607890594, Panama = -3.29416560287372, Paraguay = -6.1257588810932, Peru = 6.53944101694304, Philippines = 6.67500844049873, Portugal = -0.768444679621794, `South Africa` = 0.483165565323186, `South Rhodesia` = 1.2914342214096, Spain = -0.671156455550308, Sweden = -4.26028339866931, Switzerland = 2.48682585582808, Turkey = -2.6656824059543, Tunisia = -2.81792000502934, `United Kingdom` = -2.69241276642556, `United States` = -1.11159014595127, Venezuela = 3.63251769439362, Zambia = 9.75091377184124, Jamaica = -3.01853140824666, Uruguay = -2.26382733704987, Libya = -2.82952566381197, Malaysia = -2.97086904885857), effects = c(`(Intercept)` = -68.384296808551, pop15 = -14.2869718756147, pop75 = 7.30360935931436, dpi = -3.52149771993956, ddpi = -7.94065681116866, -0.655206619955559, -7.98426769818929, 2.11835129324918, -1.5354578825814, 4.94070903923897, 4.9811476263448, -2.36103969775486, -1.5661521693604, 1.68196909708745, -0.182551082570306, -3.28374023011935, -3.03783031104655, 0.762019243487725, -6.28806559687962, 1.15942218549724, 2.92804205826621, 2.04415604780183, 5.04587845254195, -6.2647879270342, -1.38102756737135, 2.31670197356863, -1.15880106817969, -0.209548919949984, 2.26101525601646, 0.709220205102216, -3.39023406360215, -5.44378328667935, 6.93989846010402, 6.81988853627435, -1.20929423152311, 0.996491767935397, 2.24569677287488, -0.520632156857349, -4.74503902147376, 2.40967313840561, -2.54148496023116, -2.56770845836587, -2.71221486177228, -1.81298485410907, 3.95072523713182, 9.62759991285484, -4.29977588639926, -1.63553230064561, -5.52474122081385, -3.28514163602414), rank = 5L, fitted.values = c(Australia = 10.56642023691, Austria = 11.4536140122637, Belgium = 10.951042071662, Bolivia = 6.44831912122319, Brazil = 9.32719055841199, Canada = 9.10689236257783, Chile = 8.8422306716793, China = 9.36396391486503, Colombia = 6.43170709733013, `Costa Rica` = 5.6549218215474, Denmark = 11.4497611572197, Ecuador = 5.99563130331345, Finland = 12.92108565186, France = 10.1645281711604, Germany = 12.7306992953747, Greece = 13.786168467824, Guatamala = 6.36528378971092, Honduras = 6.98997551582694, Iceland = 7.48058197743013, India = 8.49132600010512, Ireland = 7.94886935942644, Italy = 12.3532451047639, Japan = 15.8185144501534, Korea = 10.0869814447457, Luxembourg = 12.0208065666955, Malta = 12.505090217663, Norway = 11.1217853610216, Netherlands = 14.2244544897822, `New Zealand` = 8.38444518244457, Nicaragua = 6.65360339210941, Panama = 7.73416560287372, Paraguay = 8.1457588810932, Peru = 6.16055898305696, Philippines = 6.10499155950126, Portugal = 13.2584446796218, `South Africa` = 10.6568344346768, `South Rhodesia` = 12.0085657785904, Spain = 12.4411564555503, Sweden = 11.1202833986693, Switzerland = 11.6431741441719, Turkey = 7.7956824059543, Tunisia = 5.62792000502934, `United Kingdom` = 10.5024127664256, `United States` = 8.67159014595127, Venezuela = 5.58748230560638, Zambia = 8.80908622815876, Jamaica = 10.7385314082467, Uruguay = 11.5038273370499, Libya = 11.719525663812, Malaysia = 7.68086904885857), assign = 0:4, qr = structure(list(qr = structure(c(-7.07106781186548, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, 0.14142135623731, -248.120941091235, 64.0620901313718, 0.165128351395561, -0.117253943076925, -0.121936899867514, 0.041498292124025, -0.0836927527443743, -0.161898131147202, -0.19140075892791, -0.207010614896538, 0.155450240695012, -0.186249506458262, 0.102064533282303, 0.14545993287509, 0.172777180820189, 0.136718413532658, -0.182190943906419, -0.202015460986577, 0.00543952483649349, -0.108200226615121, 0.0502398114664568, 0.153889255098149, 0.115020713736264, -0.114912464681631, 0.196348063332818, 0.0286982102297497, 0.13156716106301, 0.15092338246411, 0.0276055203119457, -0.166424989378104, -0.143322402544535, -0.106170945339199, -0.15315661180477, -0.185469013659831, 0.0845814945974391, 0.0380641238109267, 0.0383763209302993, 0.103625518879166, 0.201967611481524, 0.169967406745836, -0.141137022708927, -0.183283633824223, 0.173401575058934, 0.0713131170241051, -0.187654393495439, -0.169703059131516, -0.105234353981081, 0.0975376750514007, -0.145351683820456, -0.200142278270342, -16.2139584926075, -8.208468361267, -3.77617493796019, 0.0876115456504285, -0.123991445176047, 0.0324742628761381, -0.0774961757403155, -0.0738240761695448, 0.0977743197948592, 0.155107547475184, 0.0545992517279037, 0.120271927354821, -0.234891833982489, 0.281643868164441, -0.139119350354824, -0.121822565049815, 0.0261316708293862, -0.00475795269661488, 0.176883803253687, -0.121375110291947, 0.367087953759436, -0.0609541793024463, -0.386710872116642, -0.119072481822996, -0.093071549693098, -0.0385154980516702, 0.041052595204344, -0.114994298426074, 0.149387613557561, 0.0796606261525182, 0.0235137463728522, -0.10224067862105, 0.067472299707597, 0.0999272621483305, -0.0672935781881911, -0.110519624702159, -0.312504442270379, -0.106097490965416, 0.108418027831249, -0.0319818209254472, -0.0133251299855025, 0.118700216134212, 0.153382985010363, 0.117026604084129, 0.046727936996969, -0.084880198289551, 0.0756668582882882, -0.131722597209973, 0.258604824847036, 0.0120897742619538, -7825.96369775173, -5244.98283997536, -1659.93396642261, 4224.21718621954, -0.0536035761934073, -0.35077055562151, 0.0207623401341921, 0.0236879366399189, 0.0545745559651996, 0.0114296081119295, -0.101423500131805, 0.0655969136116444, -0.0698187942331708, 0.0345569662376129, -0.141247492691575, 0.200376455993068, 0.0364124765390022, 0.0170765160579042, -0.0834728759435578, 0.113953733698577, 0.213306965476638, 0.118008933971425, -0.00866553196137767, 0.0792113815433863, -0.0970181619831277, 0.173825665030011, -0.0698459049119983, 0.0126239481371422, 0.0290805918657238, 0.0643125258094002, 0.0125921826736313, 0.0917999190055434, 0.0570877549090301, 0.0914204492762292, 0.230757469991387, 0.146950137427881, 0.170732567828158, 0.193378225888342, -0.220912223157481, -0.147702799390841, 0.0443649595718382, 0.077304219055593, 0.114947741036207, -0.529085028782653, -0.0863493470870069, 0.0469190526616599, 0.11777662604228, 0.178113267059554, 0.198657880592627, 0.0226743924701606, -26.5702444098657, -0.960774896257385, 0.871339488314517, -5.12174037679466, -19.3818772725331, -0.0342852848366908, -0.050612321042065, 0.151684286261799, -0.0196288590772824, -0.0273668123524811, 0.0198202468033202, -0.0658872227213478, 0.0258944985383431, 0.0450479043578137, -0.0136507065100683, 0.106740475035809, -0.103928040664259, -0.0141841059200206, -0.116828148616797, -0.117123520487969, -0.0404334605775779, -0.0262720701160171, 0.214858348707238, 0.106568493847888, -0.113364845360484, 0.213045488244538, -0.00114815133568938, 0.193245329389977, -0.0955666175455098, -0.0534734806249023, 0.00574774495172758, -0.140940531212752, -0.147448750016385, -0.0786961245719627, 0.171057803856445, -0.0939467507263722, -0.11359148283, 0.010171477682808, -0.0211367673646394, -0.0469846629052428, -0.0320113781263437, -0.121786835708436, -0.0977217117448339, -0.016588388025142, -0.141504675692516, 0.0790414331106965, 0.338378959036943, -0.116640440486279, 0.675176165764421, 0.0834079960915886 ), dim = c(50L, 5L), dimnames = list(c("Australia", "Austria", "Belgium", "Bolivia", "Brazil", "Canada", "Chile", "China", "Colombia", "Costa Rica", "Denmark", "Ecuador", "Finland", "France", "Germany", "Greece", "Guatamala", "Honduras", "Iceland", "India", "Ireland", "Italy", "Japan", "Korea", "Luxembourg", "Malta", "Norway", "Netherlands", "New Zealand", "Nicaragua", "Panama", "Paraguay", "Peru", "Philippines", "Portugal", "South Africa", "South Rhodesia", "Spain", "Sweden", "Switzerland", "Turkey", "Tunisia", "United Kingdom", "United States", "Venezuela", "Zambia", "Jamaica", "Uruguay", "Libya", "Malaysia"), c("(Intercept)", "pop15", "pop75", "dpi", "ddpi")), assign = 0:4), qraux = c(1.14142135623731, 1.1726210822605, 1.16459675512416, 1.15395548271583, 1.0534577838838 ), pivot = 1:5, tol = 1e-07, rank = 5L), class = "qr"), df.residual = 45L, xlevels = structure(list(), names = character(0)), call = lm(formula = sr ~ ., data = LifeCycleSavings), terms = sr ~ pop15 + pop75 + dpi + ddpi, model = structure(list(sr = c(11.43, 12.07, 13.17, 5.75, 12.88, 8.79, 0.6, 11.9, 4.98, 10.78, 16.85, 3.59, 11.24, 12.64, 12.55, 10.67, 3.01, 7.7, 1.27, 9, 11.34, 14.28, 21.1, 3.98, 10.35, 15.48, 10.25, 14.65, 10.67, 7.3, 4.44, 2.02, 12.7, 12.78, 12.49, 11.14, 13.3, 11.77, 6.86, 14.13, 5.13, 2.81, 7.81, 7.56, 9.22, 18.56, 7.72, 9.24, 8.89, 4.71), pop15 = c(29.35, 23.32, 23.8, 41.89, 42.19, 31.72, 39.74, 44.75, 46.64, 47.64, 24.42, 46.31, 27.84, 25.06, 23.31, 25.62, 46.05, 47.32, 34.03, 41.31, 31.16, 24.52, 27.01, 41.74, 21.8, 32.54, 25.95, 24.71, 32.61, 45.04, 43.56, 41.18, 44.19, 46.26, 28.96, 31.94, 31.92, 27.74, 21.44, 23.49, 43.42, 46.12, 23.27, 29.81, 46.4, 45.25, 41.12, 28.13, 43.69, 47.2), pop75 = c(2.87, 4.41, 4.43, 1.67, 0.83, 2.85, 1.34, 0.67, 1.06, 1.14, 3.93, 1.19, 2.37, 4.7, 3.35, 3.1, 0.87, 0.58, 3.08, 0.96, 4.19, 3.48, 1.91, 0.91, 3.73, 2.47, 3.67, 3.25, 3.17, 1.21, 1.2, 1.05, 1.28, 1.12, 2.85, 2.28, 1.52, 2.87, 4.54, 3.73, 1.08, 1.21, 4.46, 3.43, 0.9, 0.56, 1.73, 2.72, 2.07, 0.66), dpi = c(2329.68, 1507.99, 2108.47, 189.13, 728.47, 2982.88, 662.86, 289.52, 276.65, 471.24, 2496.53, 287.77, 1681.25, 2213.82, 2457.12, 870.85, 289.71, 232.44, 1900.1, 88.94, 1139.95, 1390, 1257.28, 207.68, 2449.39, 601.05, 2231.03, 1740.7, 1487.52, 325.54, 568.56, 220.56, 400.06, 152.01, 579.51, 651.11, 250.96, 768.79, 3299.49, 2630.96, 389.66, 249.87, 1813.93, 4001.89, 813.39, 138.33, 380.47, 766.54, 123.58, 242.69), ddpi = c(2.87, 3.93, 3.82, 0.22, 4.56, 2.43, 2.67, 6.51, 3.08, 2.8, 3.99, 2.19, 4.32, 4.52, 3.44, 6.28, 1.48, 3.19, 1.12, 1.54, 2.99, 3.54, 8.21, 5.81, 1.57, 8.12, 3.62, 7.66, 1.76, 2.48, 3.61, 1.03, 0.67, 2, 7.48, 2.19, 2, 4.35, 3.01, 2.7, 2.96, 1.13, 2.01, 2.45, 0.53, 5.14, 10.23, 1.88, 16.71, 5.08)), terms = sr ~ pop15 + pop75 + dpi + ddpi, row.names = c("Australia", "Austria", "Belgium", "Bolivia", "Brazil", "Canada", "Chile", "China", "Colombia", "Costa Rica", "Denmark", "Ecuador", "Finland", "France", "Germany", "Greece", "Guatamala", "Honduras", "Iceland", "India", "Ireland", "Italy", "Japan", "Korea", "Luxembourg", "Malta", "Norway", "Netherlands", "New Zealand", "Nicaragua", "Panama", "Paraguay", "Peru", "Philippines", "Portugal", "South Africa", "South Rhodesia", "Spain", "Sweden", "Switzerland", "Turkey", "Tunisia", "United Kingdom", "United States", "Venezuela", "Zambia", "Jamaica", "Uruguay", "Libya", "Malaysia" ), class = "data.frame")), class = "lm")): could not find function "infl_like"