[R] problem with lm, and summary.lm
Tolga Uzuner
tolga.uzuner at gmail.com
Sun Nov 16 18:20:27 CET 2008
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 at 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
>>
>> ______________________________________________
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>> 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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