similar to: demo(scoping)

it takes a long time to load the lme4 package.anyone else encounter this problem? > system.time(library(lme4)) 佋佖伻侂佇佽佉仾伒伳伋佁伡伃伆侟仯伜Matrix 佋佖伻侂佇佽佉仾伒伳伋佁伡伃伆侟仯伜lattice [1] 19.90 0.30 25.56 NA NA > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status Patched major 2 minor

It is not a pure R question,but I hope some one can give me advices. I want to use analysis my data with the multilevel model.The data has 2 levels---- the second level has 52 units and each second level unit has 19-23 units.I think the sample size is quite small,but just now I can't make the sample size much bigger.So I want to ask if I use the multilevel model to analysis the data set,will

the data file has such structure: 1992 6245 49 . . 20 1 0 0 8.739536 0 . . . . . . . . "alabama" . 0 . 1993 7677 58 . . 15 1 0 0

Hi, Given a frame with calendar date's: "2005-07-01", "2005-07-02","2005-07-03","2005-07-04","2005-07-05",etc. I want to extract the following from these dates: week number month number year number Any ideas how to accomplish this? Many thanks. Regards, Richard

i study the code of function ave,but i can understand one line of the syntax. > ave function (x, ..., FUN = mean) { n <- length(list(...)) if (n) { g <- interaction(...) split(x, g) <- lapply(split(x, g), FUN) } else x[] <- FUN(x) x } my question is : what does "split(x, g) <- lapply(split(x, g), FUN)" mean? thank you! --

The green book tells:"The basic technique is classic :keep it simple ."A long ,complicated expression or function is less fravorable than" a relatively small computations that combines calls to a few other functions to perform its tasks." But I don't get the point totally.Can anyone give me an example to make me understand this rules totally? ps: Is it mean that f1 is

data from multilevel units,first sample the class ,and then the student in calss.following is the 2-level model. and the level-1 model deals with the student,and the level-2 model deals with the class level the students belong to. Level-1 Model Y = B0 + B1*(ZLEAD) + B2*(ZBUL) + B3*(ZSHY) + R Level-2 Model B0 = G00 + U0 B1 = G10 + G11*(ZWARMT) + U1 B2 = G20 + G21*(ZWARMT) + G22*(ZABLET) +

======= 2005-12-06 22:16:17 伳侜佋佢伬伌佇伵佒佇佇伌伒伬仯伜======= >Martin Maechler a 侀crit : > >> please, please, these trailing ";" are *so* ugly. >> This is GNU S, not C (or matlab) ! >> >> but I'll be happy already if you could >> drop these ugly empty statements at the end of your lines... > >May I disagree ? >I find missing ";" at

> library(foreign) > da<-read.dta(file.choose()) > da startdat starttim enddate endtime days hoursmin secused 1 2005-01-11 2 2005-12-15 20.19 NA NA 9 > attributes(da) $datalabel [1] "Example of use of date and time functions" $time.stamp [1] "15 伿伄伓侢佋伮 2005 20" $names [1] "startdat" "starttim"

In this case the environment contains the variables local to the function, and its enclosure is the environment of the enclosing function.(R-lang:p11) I want to know if the "enclosing function" means the closure of the function? for example ,if I call function mean(),and the create an environment,say e1,then the enclosure of e1 is the namespace of base package? Right? Thank you!

Hi, I wonder how well SPSS and R communicate, because I need SPSS but would like to do some data manipulations in R. However I am very afraid of never ending import-export-complications ? especially with all those labels and extra information my SPSS files contain. My data come from SPSS and have to be exported to SPSS again (because I need to produce special output tables, which would be hard to

Dear R users, I have two related questions about scoping and data encapsulation. One is fairly specific - I am looking at "scoping.R" which is used in demo(scoping) - it's an example of lexical scoping and encapsulation. Where is the 'total' stored? It is not an attribute in 'ross' or 'robert' however, functions like balance() have access to it. Is it more

Dear R-list, I have a dataset, say (the real dataset is 20 columns,110200 rows). > my.reducedID V1 V2 V3 V4 V5 V6 V7 V8 V9 [1,] 1 0 0 1 14 3 1 0 2 [2,] 2 0 0 1 14 3 1 0 2 [3,] 0 1 0 1 14 2 1 0 2 [4,] 0 0 1 1 14 3 1 0 2 [5,] 0 1 1 0 14 2 1 0 2 [6,] 0 0 0 1 14 3 1 0 2 [7,] 0 0 0 1 0 3 1 0 2 [8,] 0

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL

the help page says: 'is.list' returns 'TRUE' iff its argument is a 'list' _or_ a 'pairlist' of 'length' > 0, whereas 'is.pairlist' only returns 'TRUE' in the latter case. does the "latter case" mean a 'pairlist' of 'length' > 0? but > is.pairlist(pairlist()) [1] TRUE > length(pairlist())

Hi, I'm using R for some arima models. In the past I used for arima models Rats and Tsp. Using the R arima function, I get only the statistics sigma^2 and log likelihood; with Rats and Tsp it is possible to obtain more statistics, such as R, R square, Durbin Watson, standard error, etc. Is it possible using R to have the statistics mentioned? My best regards,

Hi guys, I have a large number of columns of a dataframe that I want to apply a common factorization to; the columns are all numeric and the factorization collapses some of these values into common groups (labels). How can I do this systematically? Is there an analog to sapply that can pass columns as vectors to FUN? Thanks in advance, Gregory Gentlemen ---------------------------------

Hello, I'm currently using a tool that provides a Loess fitting, but I obtained results that are slightly different from those provided by R implementation of the Loess. That's why I would like to know if you could give me a source (bibliography or web) that explains in a clear way each step of the algorithm, with the possible options to choose, etc.. in order for me to understand those

All, I'm having a problem selecting directly from a vector. I've written ways to do this indirectly, but I'd rather do it directly and didn't see this in the manual. Essentially, I have: > group.label.new [1] 7 9 6 1 10 4 8 3 2 5 > junk [1] 1 2 > group.label.new[junk && 8:10] [1] 7 9 6 1 10 4 8 3 2 5 I'd like to select the elements

Dear all, I have a date frame like this: X Y Z 22 24 4.3 2.3 3.4 5.3 ..... .... 57.2 23.4 34 What my purpose is: to sort the data frame by either X, Y or Z. sample output is (sorted by X) : X Y Z 2.3 3.4 5.3 ..... ...... 22 24 4.3 ... 57.2 23.4 34 I have no idea how to use sort, order or rank functions. Please help me out. Thanks! Leaf