search for: degf

Hi R-users,   I have this code below and use some code from sn package for multivariate skew t (rmst) to generate a set of random numbers.   I try to do a looping to produce ‘rand’ for different values of degrees of freedom (degf).  Actually, I’m not sure how to specify the attribute for the rand.  As we know, rand will give us a set of results + all the parameters used, so just wonder whether we can do the same for this iteration.   rand_skewt <- function(dt,degf,n) { t1    <- length(degf)   rand  <- matrix(dt,nro...

Hi list-members can anybody tell me why > pairwise.t.test(val, fac) produces an empty p-table. As shown below: Pairwise comparisons using t tests with pooled SD data: val and fac AS AT Fhh Fm Fmk Fmu GBS Gf HFS Hn jAL Kol R_Fill AT - - - - - - - - - - - - - Fhh - - - - - - - - - - - - - Fm - - - - - - -

...quot; and I would like to get the hourly average of the "mph" for the summer months (spanning all years). I have been trying to use "aggregate" but am not having much success at all! any thoughts would be greatly appreciated. thanks- sherri LST inch mph Deg DegF DegF % volts Deg mph w/m2 0506010000 0.00 13.6 218.1 36.8 -999 65.1 -999 -999 18.2 0.2 0506010005 0.00 12.9 214.3 36.8 -999 65.5 -999 -999 16.9 0.2 0506010010 0.00 14.4 215.7 36.9 -999 65.4 -999 -999 20.4 0.2 0506010015...

...ferent date formats and different times zones. I need to match up the date/time of the datasets and then invoke a conditional statement, such as: if dataC$mph is >= 12 then keep dataM$co23 for the corresponding time/date stamp. snippets of data files: *dataC.txt* LST in mph Deg DegF DegF2 % volts Deg mph2 w/m2 0506010000 0.00 13.6 218.1 36.8 -999 65.1 -999 -999 18.2 0.2 0506010005 0.00 12.9 214.3 36.8 -999 65.5 -999 -999 16.9 0.2 0506010010 0.00 14.4 215.7 36.9 -999 65.4 -999 -999 20.4 0.2 *dataM.txt...

...nG3 = sum(Group %in% G3) G3Mean = mean(Var[Group %in% G3]) MScontr = (nG1 * ((G1Mean - GrandMean)^2) + nG2 * ((G2Mean - GrandMean)^2) + nG3 * ((G3Mean - GrandMean)^2))/2 } An <- anova(lm(Var ~ Group)) MSwithin = An[3]['Residuals',] DegF = An$Df[length(An$Df)] Fval = MScontr / MSwithin Pval = 1 - pf(Fval, 1, DegF) return (list(MS_contrasts = MScontr, MS_within = MSwithin, F_value = Fval, P_value = Pval)) } ## The first two contrasts produce the same (+/- rounding error) ## p-values as obtained using contrasts()...

...he right direction. I have included a reproducible example from part of the data. The problem appears to be the lack of data in column POH which I can see when I cross tab the data xtabs(IWD ~ about + SOA,data=test1) (from the dummy example below) SOA about ARON CRDA DCJH DJKT DEGF DOPC FACO FRNE HHW MEPR NGA OTHE OTRE JHG POH non-I NO G 0 1 0 0 443 0 2 172 486 96 73 233 217 408 0 I NO G 1 0 0 0 251 0 0 15 545 29 0 8 698 207 0 non-I ERT 0 435 153 66 152 17 15 7 85 233 32 15 147 216 0 I...

...he right direction. I have included a reproducible example from part of the data. The problem appears to be the lack of data in column POH which I can see when I cross tab the data xtabs(IWD ~ about + SOA,data=test1) (from the dummy example below) SOA about ARON CRDA DCJH DJKT DEGF DOPC FACO FRNE HHW MEPR NGA OTHE OTRE JHG POH non-I NO G 0 1 0 0 443 0 2 172 486 96 73 233 217 408 0 I NO G 1 0 0 0 251 0 0 15 545 29 0 8 698 207 0 non-I ERT 0 435 153 66 152 17 15 7 85 233 32 15 147 216 0 I...

Hi, how can i plot two different x axis in a ggplot2 qplot? I want to plot Farenheit and Celsius in one diagram. x1:Farenheit x2:Celsius kind regards, -- Jonas Stein <news at jonasstein.de>

Hi R-users, I am trying to automate the daily running of a simple R script from Windows 7. >From previous posts, I understand that this needs to be done with the task scheduler. I can schedule my laptop to automatically open R at a certain time, but not to execute a script. Secondary question: how do I save a list of R commands so that they get executed once the file is open? Right now, I

...a in both R and stata x <- read.dta( "http://www.ats.ucla.edu/stat/stata/library/apiclus1.dta" ) dclus1<-svydesign(id=~dnum, fpc=~fpc, data=x) # mean matches exactly coef(svymean(~I(ell==0), dclus1)) # SE matches exactly SE(svymean(~I(ell==0), dclus1)) # design df matches exactly degf(dclus1) # unwtd count matches exactly unwtd.count( ~ell, dclus1) # wtd count matches exactly svytotal( ~!is.na(ell), dclus1) # number of clusters match exactly dclus1 # none of the confidence interval options match exactly # the standard confint() will certainly be wrong, # since stata gives...