search for: m01

...body! I'm sure that I overlook something and feel quite stupid to ask, but I have not found an easy solution to the following problem: Take e.g. the Orthodont data from the nlme package: > head(Orthodont) Grouped Data: distance ~ age | Subject distance age Subject Sex 1 26.0 8 M01 Male 2 25.0 10 M01 Male 3 29.0 12 M01 Male 4 31.0 14 M01 Male 5 21.5 8 M02 Male 6 22.5 10 M02 Male Suppose now, that I have a vector which contains the names of the "meta"-fields in this data-frame: metaFields <- c("Subject", &q...

...ing example: library(nlme) fm3 <- lme(distance ~ age*Sex, data = Orthodont, random = ~ 1) df3.1 <- with(Orthodont, data.frame(age=seq(5, 20, 5), Subject=rep(Subject[1], 4), Sex=rep(Sex[1], 4))) predict(fm3, df3.1, interval='prediction') # M01 M01 M01 M01 # 22.69012 26.61199 30.53387 34.45574 # NOTE: The 'interval' argument to the 'predict' function was ignored. # It works works for an 'lm' object, but not an 'lme' object. One way to do this might be via mcmcsamp of the correspond...

...------------------------------------- d0 <- data.frame(a = numeric(0)) # zero length data.frame d00 <- unname(d0) # zero length data.frame __without names__ d3 <- data.frame(a=1:3) # non-empty data.frame d30. <- d3[,FALSE] # 3 x 0 -- take into account, too ! d30 <- unname(d30.) m01. <- matrix(,0,1, dimnames=list(NULL,"a")) # 0 x 1 matrix with dimnames m01 <- unname(m01.) m00. <- matrix(,0,0, dimnames=list(NULL,NULL)) # 0 x 0 matrix with dimnames m00 <- unname(m00.) m3 <- data.matrix(d3) ##------------------------ ## error A: ## Error in matrix(if (is....

Sorry, I can't reproduce the example below even on the same machine. However, the following example produces the same error as NULL values in prior examples: > setClass("FOOCLASS", +????????? representation("list") + ) > ma = new("FOOCLASS", list(M=matrix(rnorm(300), 30,10))) > isS4(ma) [1] TRUE > data.frame(a=1:3) == ma Error in

...ne is going to be > > rewriting lme to use model.frame: it is essentially in maintainence mod= e.) > > Another workaround is to use poly(..., raw=3DTRUE). I don't actually see > anything in this report using predict.lme, but compare > > > predict(fm, Newdata) > M01 M01 M01 M01 M02 M02 > 21.01353 25.63852 32.30504 38.59640 17.24007 21.86507 > attr(,"label") > [1] "Predicted values (mm)" > > fm <- lme(distance ~ poly(age, 3, raw=3DTRUE) + Sex, data =3D Orthodont= , > random =3D ~1) &...

...80 10 0 329 C07 CP2 CP 180 10 0 330 C07 CP2 CP 180 10 0 331 C07 CP2 CP 180 10 0 332 C07 CP2 CP 180 10 0 333 C07 CP2 CP 180 10 0 334 C07 CP2 CP 180 10 0 335 C07 CP2 CP 180 10 0 336 C07 CP2 CP 180 10 0 337 C07 CP2 CP 180 10 0 338 C07 CP2 CP 180 10 0 339 C07 CP2 CP 180 10 0 340 C07 CP2 CP 180 10 0 341 M01 MT1 MT 180 10 1 342 M01 MT1 MT 180 10 1 343 M01 MT1 MT 180 10 0 344 M01 MT1 MT 180 10 0 345 M01 MT1 MT 180 10 0 346 M01 MT1 MT 180 10 0 347 M01 MT1 MT 180 10 0 348 M01 MT1 MT 180 10 0 349 M01 MT1 MT 180 10 0 350 M01 MT1 MT 180 10 0 351 M01 MT1 MT 180 10 0 352 M01 MT1 MT 180 10 0 353 M01 MT1 MT 180...

...d land and water, and for the category that appears in both m1 and m2 the end result will be a sum. results will be m3: cat1 cat2 cat3 cat4 cat5 cat6 land 45 78 47 48 35 36 water 21 34 23 24 15 16 To do this i thought in making an empty matrix for each m1 and m2 (called m01 and m02 respectively) with 6 columns and 2 rows, and do a long if else statement in which i match the name of the first column in m1 with the name of the first column in m01 and if they match get the data from m1, if not leave it 0 and so on. Same thing for m2 and m02. This is long and extremely cl...

...ct is not subsettable > fm2 <- update(fm2, . ~ .) # this replaces "mod" by the contents of variable mod > fm2 Linear mixed-effects model fit by REML Data: Orthodont Log-restricted-likelihood: -218.7563 Fixed: distance ~ age + Sex ... > predict(fm2, Orthodont) M01 M01 M01 M01 ... 25.39237 26.71274 28.03311 29.35348 21.61052 ... > fm2 <- lm(mod, data = Orthodont) > predict(fm2, Orthodont) 1 2 3 4 ... 22.98819 24.30856 25.62894 26.94931 ...

Hi, I am trying to run a panel regression where I have a matrix of observations and a matrix of independant variables - examples would trying to predict countries's GDP with their data on education, FDI, tax rates, over time. For the purpose of simplicity, my data would be: dep = matrix(rnorm(50),ncol=5) indep1 = matrix(rnorm(50),ncol=5) indep2 = matrix(rnorm(50),ncol=5) >From what I

...appropriate permissions to access the item. Checking the security of that file I do not see any mention of the domain to which the computer has been added and logged on to. In security I see: ALL APPLICATION PACKAGES rx r ALL RESTRICTED APPLICATION PACKAGES rx r SYSTEM rx r Administrators (AKL-M01)\Administrators) rx r Users (AKL-M01\Users) rx r TrustedInstaller f m rx r w Ctrl Pnl -> Admin tools -> Comp Mgmt -> Local Users and Groups -> Groups -> Administrators show that BROCKLEY\Domain Admins is a member. So I checked samba and this is what I discovered: [root at smb4-2 ~...

...e data "Orthodont" are grouped. > show(dolf) distance age Subjectt Sex 1 6.83679 22.01 F1 F 2 6.63245 23.04 F1 F 3 11.58730 39.26 M2 M > show(Orthodont) Grouped Data: distance ~ age | Subject distance age Subject Sex 1 26.0 8 M01 Male 2 25.0 10 M01 Male 3 29.0 12 M01 Male -- View this message in context: http://r.789695.n4.nabble.com/grouping-data-tp3679803p3679803.html Sent from the R help mailing list archive at Nabble.com.

...11.11 machine, as test for migration plan. The data on the source is not changing since it is snapshot of active data. Every time we try to run the following command: timex rsync -avuz --delete isynh09:/snap We get the following error: receiving file list ... done mknod "/d/snap/m01/server_metadata/postgresql/.s.PGSQL.5432" failed: Invalid argument mknod "/d/snap/m02/server_metadata/postgresql/.s.PGSQL.5432" failed: Invalid argument mknod "/d/snap/m03/server_metadata/postgresql/.s.PGSQL.5432" failed: Invalid argument mknod "/d/snap/m04/server_m...

...ts for each subgroup (in this example - each subject). For example, for MO1 it's: 1.25 for intercept, 0.106 for age, and -1.52 for SexFemale. So, in order to get the the total effects, i.e., the regression equation, for each subgroup (Subject) I need to do this: For example, for Subject MO1: y(M01) = (17.71+1.25)+(0.66+0.106)*Age+(-1.66-1.52)*SexFemale = 18.96 + 0.766*Age -3.18*SexFemale Question: Is there an easier way to get such an equation for each level of Subject? Thank you very much! -- Dimitri Liakhovitski Ninah Consulting www.ninah.com

...th of year) * value * footnote_codes The series_id consists of five fixed-width subfields (length in parentheses): * survey abbreviation (2) * seasonal code (1) * area type code (2) * area code (6) * measure code (2) So an example record might be: LASPS36040003 1990 M01 8.8 L I want to read in the data in one pass and convert them to a data frame with the following columns (actual name, class in parentheses): Survey abbreviation (survey, character) Seasonal (seasonal, logical seasonal=T) Area type (area_type_code, factor) Area (area_code, factor)...

...and returning errors. # cat /etc/fstab LABEL=/ / ext3 defaults 1 1 LABEL=/opt /opt ext3 defaults 1 2 LABEL=/home /home ext3 defaults 1 2 LABEL=/tmp /tmp ext3 defaults 1 2 LABEL=/var /var ext3 defaults 1 2 LABEL=/usr /usr ext3 defaults 1 2 LABEL=/usr/local /usr/local ext3 defaults 1 2 LABEL=/m01 /m01 ext3 defaults 1 2 LABEL=/boot /boot ext3 defaults 1 2 tmpfs /dev/shm tmpfs defaults 0 0 devpts /dev/pts devpts gid=5,mode=620 0 0 sysfs /sys sysfs defaults 0 0 proc /proc proc defaults 0 0 LABEL=SWAP-sda3 swap swap defaults 0 0 #3600508b4000a233c00006000010e0000 -> dm-0 /dev/mapper/mpath1p1...

Hi All, I am new to post question on this list. I apologize if this question is too easy or irrelevant. I am doing a simulation study and I need to read a data file that can be easily read by SAS. So, what I try to do is to execute SAS in R and then read the output of SAS to R. I try the following code but it didn't work. system("c:\\program files\\sas institute\\v8\\sas.exe

...ains INITIAL values). ---------------------Start R-code & output ------------------------------- #This intilizes a 2-banded Toeplitz structure cs1ARMA <- corARMA(value = c(0,-.3), form = ~ 1 | Subject, p = 2, q = 0) cs1ARMA <- Initialize(cs1ARMA, data = Orthodont) corMatrix(cs1ARMA)$M01 [,1] [,2] [,3] [,4] [1,] 1.0 0.0 -0.3 0.0 [2,] 0.0 1.0 0.0 -0.3 [3,] -0.3 0.0 1.0 0.0 [4,] 0.0 -0.3 0.0 1.0 > TOEP2 <- gls(distance ~ Sex * I(age - 11), Orthodont, + correlation = corARMA(value = c(0,-.3), form = ~ 1 | Subject, p = 2, q = 0), +...

...ains INITIAL values). ---------------------Start R-code & output ------------------------------- #This intilizes a 2-banded Toeplitz structure cs1ARMA <- corARMA(value = c(0,-.3), form = ~ 1 | Subject, p = 2, q = 0) cs1ARMA <- Initialize(cs1ARMA, data = Orthodont) corMatrix(cs1ARMA)$M01 [,1] [,2] [,3] [,4] [1,] 1.0 0.0 -0.3 0.0 [2,] 0.0 1.0 0.0 -0.3 [3,] -0.3 0.0 1.0 0.0 [4,] 0.0 -0.3 0.0 1.0 > TOEP2 <- gls(distance ~ Sex * I(age - 11), Orthodont, + correlation = corARMA(value = c(0,-.3), form = ~ 1 | Subject, p = 2, q = 0), +...

...ains INITIAL values). ---------------------Start R-code & output ------------------------------- #This intilizes a 2-banded Toeplitz structure cs1ARMA <- corARMA(value = c(0,-.3), form = ~ 1 | Subject, p = 2, q = 0) cs1ARMA <- Initialize(cs1ARMA, data = Orthodont) corMatrix(cs1ARMA)$M01 [,1] [,2] [,3] [,4] [1,] 1.0 0.0 -0.3 0.0 [2,] 0.0 1.0 0.0 -0.3 [3,] -0.3 0.0 1.0 0.0 [4,] 0.0 -0.3 0.0 1.0 > TOEP2 <- gls(distance ~ Sex * I(age - 11), Orthodont, + correlation = corARMA(value = c(0,-.3), + form = ~ 1 | Subject, p = 2,...

Hi, I am doing a binomial GLMM with a random intercept using the formula below, but I always get the same warning message. > m01 <- lmer(pres~ HT + DN + dtree + DNm + cmnhi + cmxes + cplan + craan + lfphal0100 + lfov0100 + lfop0100 + (1|plot), family=binomial, data=vphal, verbose=TRUE) 0: 6309.9448: 0.459924 -5.20747 -0.378722 0.558779 -0.200922 -0.0488451 -0.397844 0.367916 -2.09820 0.233011 0.489537 0.156096 0.233...