similar to: P-value for F from summary.lm (was RE: (no subject))

hi, can anyone help me about the simple data probability-value of the F-test, respectively p-value, shown in the summary of a linear model? somehow i can not retrieve this data out of R+ into my sql-dataset. i can get all other data shown with the command: summary(speciallinearmodel) - will have a gui screen Call: lm(formula = y21 ~ x4 + x18 + x4:x18, data = clustertransformationstabelle)

please help me. since 2 days i have tried desperately to find desperately a solution for the following problem: i have an array of 3 different vectors like: > clustertransformationstabelle[,15:17] x1 x2 x3 1 0.6270023 0.2464946 0.5074781 2 0.5629291 0.1783861 0.4398626 3 0.6773455 0.3107641 0.5637289 4 0.0000000 0.0000000 0.0000000 i want to calculate

R developers, I have a first attempt to make an aov function. Eventually I want to build in Error() structure, but first I am trying to get this presentable for balanced data with only a single stratum, just using residual error. I am following R. M. Heiberger's Computation for the Analysis of Designed Experiments, Wiley (1989) I a using a wrapper (aov.bal) to call the

Hi, I have a list called ds which has the following attributes: attributes(ds) $names [1] "adj.r.squared" "fstatistic" "intercept" "slope" [5] "std.error" "tstatistic" I want to replace all the NaN is ds with 0, and after searching past posts I found I can hardcode it like this:

could someone explain why the name of FPVAL gets " .value" concatenated onto it when the code below is run and temp is returned. I've been trying to figure this out for too long. It doesn't matter when I put the FPVAL in the return statement. It happens regardless of whether it's first or last. Thanks. f.lmmultenhanced <- function(response, pred1, pred2) {

Dear Sir or Madam, I am a student at MSc Probability and Finance at Paris 6 University/ Ecole Polytechnique. I am using R and I can't find an answer to the following question. I will be very thankful if you can answer it. I have two vectors rendements_CAC40 and rendements_AlcatelLucent. I use the lm function as follows, and then the sumarry function: regression=lm(rendements_CAC40 ~

inputfille snpid indid genotype gvariable probeid gene geneexpression rs1040480 CHB_NA18524 C/T 2 GI_19743926-I PTPRT 5.850586 rs1040480 CHB_NA18526 C/C 1 GI_19743926-I PTPRT 6.028641 rs1040480 CHB_NA18529 C/C 3 GI_19743926-I PTPRT 5.944392 rs1040481 CHB_NA18532 C/C 1 GI_19743926-I PTPRT 5.938578 rs1040481 CHB_NA18537 C/C 2 GI_19743926-I PTPRT 5.874439 rs1040481 CHB_NA18540 C/C 3 GI_19743926-I

For every specific V1 and V4 pair (ex:A and P) calculate Linear regression of V3(y-axis) and V2(x-axis) and print p value along with the pair (output). INPUT ############# V1 V2 V3 V4 A 1 2.5 P A 2 2.8 P A 3 3.2 P A 2 1.1 Q A 3 1.7 Q A 1 2.2 Q B 1 2.5 P B 2 2.9 P B 3 3.0 P SCRIPT ####### data1<-read.table("INPUT", header=TRUE) fm <- lmList(V3~V2|V1,V4 data=data1) get.pval <-

Dear all, I am not fluent in R and am struggling to 1) apply a lm to a weight-size dataset, thus the model has to run separately for each species, each year; 2) extract coefs, r-squared, n, etc. The data look like this: year sps cm w 2009 50 16 22 2009 50 17 42 2009 50 18 45 2009 51 15 45 2009 51 16 53 2009 51 17 73 2010 50 15 22 2010 50 16 41 2010 50 16 21 2010

Dear R users I have run an regression and want to extract the p value of the F statistics, but I can find a way to do that. x<-summary(lm(log(RV2)~log(IV.m),data=b)) Call: lm(formula = log(RV2) ~ log(IV.m), data = b[[11]]) Residuals: Min 1Q Median 3Q Max -0.26511 -0.09718 -0.01326 0.11095 0.29777 Coefficients: Estimate Std. Error t value Pr(>|t|)

Hello I am trying to get out of an lm model the fstatistics, however after I run the model I write > names(Model) and the fstatistic does not appear only these. names(Model) [1] "coefficients" "residuals" "effects" "rank" "fitted.values" [6] "assign" "qr" "df.residual"

Just to inform: I posted that before in R-sig-ecology but as it might be interesting also for other useRs, I post it also to the general r-user list: Hello Alexandre, thank you very much. I also found another way to extract summarizing information from lm results over e.g. 1000 repeated model runs: results2 <- t(as.data.frame(results)) summary(results2) Although some questions popped up in

I'd like to automatically plot the p-value and r^2 of a linear model. I know that I can extract r^2 with foo <- lm(y~x) a <- summary(foo) a$r.squared I can't find any similar functionality to obtain the p-value based on the ftest a$fstatistic returns the actual f-test and df, but not the p-value. Any thoughts? Thanks, Adam using R-0.65.1 Win32

Hi everyone, I'm trying to determine the significance of a trendline. From my internet search months ago, I came across the following post. I modified tim and dat for simiplicity. tim <- 1:10 dat <- c(0.17, 1.09 ,0.11, 0.82, 0.23, 0.38 ,2.47 ,0.41 ,0.75, 1.44) fstat <- summary(lm(dat~tim))$fstatistic p.val <-

Hi all, I'm struggling with nls. How do you know if your model is significant? For a lm, you get a p-value, but you don't get it for a nls. Is there a way to calculate it? For a lm I use this: a<-summary(lm(model ~obs)) f.stat<-a$fstatistic p.value<-1-pf(f.stat["value"],f.stat["numdf"],f.stat["dendf"]) Is there something similar for a nls?

Hi, A following function was kindly provided by GGally?s maintainer, Barret Schloerke. function(data, mapping, ...) { p <- ggplot(data = data, mapping = mapping) + geom_point(color = I("blue")) + geom_smooth(method = "lm", color = I("black"), ...) + theme_blank() + theme(panel.border=element_rect(fill=NA, linetype =

Hi there, I am stuck trying to solve what should be a fairly easy problem. I have a data frame that essentially consists of (ID, time as seqMonth, variable, value) and i want to find the regression coefficient of value vs time for each combination of ID and Variable. I have tried several approaches and none of them seems to work as i expected. For example, i have tried:

Kevin They do not exist. This question has come up often. Try the following to see a thread RSiteSearch('lmer p-values') Harold > -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Hai Lin > Sent: Friday, May 05, 2006 12:46 PM > To: r-help at stat.math.ethz.ch > Subject: [R] F-statistic

Dear R guru, I am Saikat Sarkar working as a researcher of Economics in Tampere University, Finland. I am trying to estimate some Garch related tests with Bayesian analysis by R programme. I am not good in R but trying to survive. Anyway I have the coding but not working properly. I have tried to find the problem but failed. I am writing to all R gurus to help me out. Could you please look at

Hi, While exploring how summary.lm generated its output I came across a section that left me puzzled. at around line 57 R <- chol2inv(Qr$qr[p1, p1, drop = FALSE]) se <- sqrt(diag(R) * resvar) I'm hoping somebody could explain the logic of these to steps or alternatively point me in the direction of a text that will explain these steps. In particular I'm puzzled