Re: [R] problem with lm, and summary.lm

From: Tolga Uzuner <tolga.uzuner_at_gmail.com>
Date: Sun, 16 Nov 2008 17:20:27 +0000

Dear Gabor,

Many thanks. That snippet of code also works for me (below). I am currently on 2.8.0.

However, it continues to fail on the specific data I am using. I have attached the data in data.RData, attached here. If you save this file into the working directory and run the following, that should illustrate the problem.

library(zoo)
load("data.RData")
regrlm<-lm(foo~bar+baz)
regrlm
summary(regrlm)

If you get the chance, would be interested to see if it fails for you as well.

Thanks again,
Tolga

############ Gabor's code ####################
 > library(zoo)
 > z <- 1:10
 > x <- z*z

 > y <- x*z
 > lm(z ~ x + y)

Call:
lm(formula = z ~ x + y)

Coefficients:
(Intercept) x y
1.24700 0.20194 -0.01164

 > summary(lm(z ~ x + y))

Call:
lm(formula = z ~ x + y)

Residuals:
Min 1Q Median 3Q Max
-0.43730 -0.14095 0.01808 0.19070 0.26702

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.246998 0.179253 6.957 0.000220 *** x 0.201943 0.015878 12.718 4.3e-06 ***
y -0.011642 0.001579 -7.375 0.000153 ***

---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1   1

Residual standard error: 0.2598 on 7 degrees of freedom
Multiple R-squared: 0.9943, Adjusted R-squared: 0.9926
F-statistic: 607.6 on 2 and 7 DF, p-value: 1.422e-08

 > sessionInfo()
R version 2.8.0 (2008-10-20)
i386-pc-mingw32

locale:
LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United 
Kingdom.1252;LC_MONETARY=English_United 
Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] lpSolve_5.6.4 leaps_2.7 nortest_1.0
[4] numDeriv_2006.4-1 bcp_2.1 snow_0.3-3
[7] fArma_270.74 fBasics_280.74 timeSeries_280.78
[10] timeDate_280.80 PerformanceAnalytics_0.9.7.1 tseries_0.10-16
[13] quadprog_1.4-11 vars_1.4-0 urca_1.1-7
[16] MASS_7.2-44 MSBVAR_0.3.2 coda_0.13-3
[19] lattice_0.17-15 xtable_1.5-4 KernSmooth_2.22-22
[22] RODBC_1.2-3 corrgram_0.1 nlme_3.1-89
[25] lmtest_0.9-21 car_1.2-9 strucchange_1.3-4
[28] sandwich_2.1-0 zoo_1.5-4

loaded via a namespace (and not attached):
[1] grid_2.8.0 tools_2.8.0
 >



Gabor Grothendieck wrote:

> Try upgrading to R 2.8.0 patched. This works for me
> using R 2.8.0 patched from Nov 10th:
>
> library(zoo)
> z <- 1:10
> x <- z*z
> y <- x*z
> lm(z ~ x + y)
> summary(lm(z ~ x + y))
>
>
>> packageDescription("zoo")$Version >>
> [1] "1.5-4"
>
>> R.version.string # Vista >>
> [1] "R version 2.8.0 Patched (2008-11-10 r46884)"
> >
> On Sun, Nov 16, 2008 at 7:32 AM, Tolga Uzuner <tolga.uzuner@gmail.com> wrote:
>
>> Dear R Users, >> >> I am having a weird problem. I have three zoo time series, foo, bar and baz. >> I run a simple linear regression with foo as the dependent and bar+baz as >> independents. Even though the regression runs fine, summary seems to >> fail.The code is below. I am happy to send the data along. I am on R 2.8.0 >> and Windows XP SP2. Traceback (below, a ton of numbers cut out to make it >> readable but I can provide the data). reveals the problem is in a function >> called gt. sessioninfo is at the bottom. >> >> Any suggestions ? I upgraded to 2.8.0 this morning after replaced 2.7.1 and >> I almost feel the new version is at fault but I could be inferring too >> much... >> >> Thanks in advance, >> Tolga >> >> cooks.distance also reveals the same problem. >> >> >>> length(foo) >>> >> [1] 258 >> >>> length(foo) >>> >> [1] 258 >> >>> length(bar) >>> >> [1] 258 >> >>> length(baz) >>> >> [1] 258 >> >>> regrlm<-lm(foo~bar+baz) >>> regrlm >>> >> Call: >> lm(formula = foo ~ bar + baz) >> >> Coefficients: >> (Intercept) bar baz 1082.39 12.72 -20176.67 >> >>> summary(regrlm) >>> >> Call: >> lm(formula = foo ~ bar + baz) >> >> Residuals: >> Error in if (xi == xj) 0L else if (xi > xj) 1L else -1L : >> argument is of length zero >> >>> traceback() >>> >> 19: .gt(c(145.181456007549, 118.279525850693, 111.250750147955, >> 89.1393551953539, >> MANY MANY NUMBERS >> -67.9948569260507, -146.080176235300), 250L, 246L) >> 18: switch(ties.method, average = , min = , max = .Internal(rank(x[!nas], >> ties.method)), first = sort.list(sort.list(x[!nas])), random = >> sort.list(order(x[!nas], >> stats::runif(sum(!nas))))) >> 17: rank(x, ties.method = "min", na.last = "keep") >> 16: as.vector(rank(x, ties.method = "min", na.last = "keep")) >> 15: xtfrm.default(x) >> 14: xtfrm(x) >> 13: FUN(X[[1L]], ...) >> 12: lapply(z, function(x) if (is.object(x)) xtfrm(x) else x) >> 11: order(x, na.last = na.last, decreasing = decreasing) >> 10: `[.zoo`(x, order(x, na.last = na.last, decreasing = decreasing)) >> 9: x[order(x, na.last = na.last, decreasing = decreasing)] >> 8: sort.default(x, partial = unique(c(lo, hi))) >> 7: sort(x, partial = unique(c(lo, hi))) >> 6: quantile.default(resid) >> 5: quantile(resid) >> 4: structure(quantile(resid), names = nam) >> 3: print.summary.lm(list(call = lm(formula = foo ~ bar + baz), terms = foo ~ >> bar + baz, residuals = c(145.181456007549, 118.279525850693, >> MANY MANY NUMBERS -97.6817272270226, -101.621851940748, -67.9948569260507, >> -146.080176235300 >> ), coefficients = c(1082.39330190496, 12.7191319384837, -20176.6660075191, >> 36.7646530199551, 0.752346859475059, 1097.00127070372, 29.4411401439708, >> 16.9059414262171, -18.3925639343844, 5.30095123419022e-84, >> 1.60626441787295e-43, >> 1.15247513614373e-48), aliased = c(FALSE, FALSE, FALSE), sigma = >> 90.0587318356495, >> df = c(3L, 255L, 3L), r.squared = 0.767559392535633, adj.r.squared = >> 0.765736328947677, >> fstatistic = c(421.027219021081, 2, 255), cov.unscaled = >> c(0.166651523684348, >> -0.00308410770161002, -3.08083131687658, -0.00308410770161002, >> 6.9788613558326e-05, 0.0263943284503598, -3.08083131687658, >> 0.0263943284503598, 148.375640597725))) >> 2: print(list(call = lm(formula = foo ~ bar + baz), terms = foo ~ >> bar + baz, residuals = c(145.181456007549, 118.279525850693, >> MANY MANY NUMBERS >> -97.6817272270226, -101.621851940748, -67.9948569260507, -146.080176235300 >> ), coefficients = c(1082.39330190496, 12.7191319384837, -20176.6660075191, >> 36.7646530199551, 0.752346859475059, 1097.00127070372, 29.4411401439708, >> 16.9059414262171, -18.3925639343844, 5.30095123419022e-84, >> 1.60626441787295e-43, >> 1.15247513614373e-48), aliased = c(FALSE, FALSE, FALSE), sigma = >> 90.0587318356495, >> df = c(3L, 255L, 3L), r.squared = 0.767559392535633, adj.r.squared = >> 0.765736328947677, >> fstatistic = c(421.027219021081, 2, 255), cov.unscaled = >> c(0.166651523684348, >> -0.00308410770161002, -3.08083131687658, -0.00308410770161002, >> 6.9788613558326e-05, 0.0263943284503598, -3.08083131687658, >> 0.0263943284503598, 148.375640597725))) >> 1: print(list(call = lm(formula = foo ~ bar + baz), terms = foo ~ >> bar + baz, residuals = c(145.181456007549, 118.279525850693, >> MANY MANY NUMBERS -97.6817272270226, -101.621851940748, -67.9948569260507, >> -146.080176235300 >> ), coefficients = c(1082.39330190496, 12.7191319384837, -20176.6660075191, >> 36.7646530199551, 0.752346859475059, 1097.00127070372, 29.4411401439708, >> 16.9059414262171, -18.3925639343844, 5.30095123419022e-84, >> 1.60626441787295e-43, >> 1.15247513614373e-48), aliased = c(FALSE, FALSE, FALSE), sigma = >> 90.0587318356495, >> df = c(3L, 255L, 3L), r.squared = 0.767559392535633, adj.r.squared = >> 0.765736328947677, >> fstatistic = c(421.027219021081, 2, 255), cov.unscaled = >> c(0.166651523684348, >> -0.00308410770161002, -3.08083131687658, -0.00308410770161002, >> 6.9788613558326e-05, 0.0263943284503598, -3.08083131687658, >> 0.0263943284503598, 148.375640597725))) >> >>> sessionInfo() >>> >> R version 2.8.0 (2008-10-20) >> i386-pc-mingw32 >> >> locale: >> LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United >> Kingdom.1252;LC_MONETARY=English_United >> Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252 >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> other attached packages: >> [1] lpSolve_5.6.4 leaps_2.7 [3] nortest_1.0 >> numDeriv_2006.4-1 [5] bcp_2.1 >> snow_0.3-3 [7] fArma_270.74 fBasics_280.74 >> [9] timeSeries_280.78 timeDate_280.80 [11] >> PerformanceAnalytics_0.9.7.1 tseries_0.10-16 [13] quadprog_1.4-11 >> vars_1.4-0 [15] urca_1.1-7 >> MASS_7.2-44 [17] MSBVAR_0.3.2 coda_0.13-3 >> [19] lattice_0.17-15 xtable_1.5-4 [21] >> KernSmooth_2.22-22 RODBC_1.2-3 [23] corrgram_0.1 >> nlme_3.1-89 [25] lmtest_0.9-21 >> car_1.2-9 [27] strucchange_1.3-4 sandwich_2.1-0 >> [29] zoo_1.5-4 >> loaded via a namespace (and not attached): >> [1] grid_2.8.0 tools_2.8.0 >> >> ______________________________________________ >> R-help_at_r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> >
>

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