similar to: Problems with basic loop

Hi All, Newbie question that i'm sure is easy, but i can't seem to apply properly I read in a datafram from a CSV file and i want to tell R that from coloum "n_0" to "n_32" the value "-1" is missing data i was looking at the is.na(xx) <- c(..,...,) idea but i can't seem to apply it properly, can anyone offer advice? On a side issue while i'm

Hi, I am getting the following build error while building llvm on RHEL5. Please help me fix this: gmake[2]: Leaving directory `/rhel5pdi/home/asin/llvm_install/tools/llvm-config' /rhel5pdi/home/asin/llvm_install/Release/bin/llvm-config: line 18: use: command not found /rhel5pdi/home/asin/llvm_install/Release/bin/llvm-config: line 19: use: command not found

On Sun, May 29, 2011 at 4:37 PM, Arjun Singri <arjunsingri at gmail.com> wrote: > Hi, > I am getting the following build error while building llvm on RHEL5. Please > help me fix this: > gmake[2]: Leaving directory > `/rhel5pdi/home/asin/llvm_install/tools/llvm-config' > /rhel5pdi/home/asin/llvm_install/Release/bin/llvm-config: line 18: use: > command not found >

Hi All, I have a table based on ordial data and i want to compare proportions and i've seen in the pwr package i can use power.prop.test however i want to find out what the sig. value is based on n1,n2,p1,p2 and this package doesn't contain this.. Does anyone know of a package that does or is it a case of writting a function specifically for this? Many thanks in advance [[alternative

Here are another three problems with logarithmic scales: 1) segments() does not work with logarithmic scales. I suggest to change lines 962-973 in "plot.c": for (i = 0; i < n; i++) { if (FINITE(xt(x0[i%nx0])) && FINITE(yt(y0[i%ny0])) && FINITE(xt(x1[i%nx1])) && FINITE(yt(y1[i%ny1]))) { GP->col = INTEGER(col)[i % ncol];

Hello useRs! I have % cover data for different plant species in 300 plots, and I use the ARCSINE transformation (to deal with % cover data). When I use a GLM I do not have any problem. But when I am trying to use a GAM model using mgcv package, to account for non-linearity I get an ?error message?. I use the following model: sp1.gam<-gam(asin(sqrt(0.01*SP1COVER))~

Hi all, Can I run a cointegrating regression, for example delta Xt=a1(Yt-1-cXt-1)+E1t and delta Yt=-b1(Yt-1-cXt-1)+E2t with R were Xt and Yt are non stationary time series at t a,b,c are parameters and E1t and E2t are error terms at t. Yt-Xt is stationary Any suggestions are welcome. Best regards, /fb -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Hi all, I want to estimate parameters from a VARMA(p,q)-Modell. The equations of the model or the model structures is given by: Xt=beta1+beta2*Xt-1+beta3*Yt-1+epsilon1 Yt=beta4+beta5*Yt-1+espilon2 epsilon1 and espilon2 are white noise. Xt is given by a vector of n elements e.g. (2, 4, 7, 9, …,n)’ and Yt is given by a vector of n elements e.g. (4,9,12,17,…,n)’. The lineVar from

I have been trying to preform both a bartlett's test and an arcsine transformation on some average percentage data. I've tried inputting it different ways and I keep getting the same error message: > head(workingdata) DYAD BEFORE AFTER 1 BG-FL 4.606772 5.787520 2 BG-LL 5.467503 7.847395 3 AD-MV 5.333735 11.107380 4 MM-FL 5.578708 12.063500 5 MM-MV 2.037605 6.415303 6 MM-RM

Hi R-users, I am using arima to fit a time series. Now I would like to include an intervention component "It (0 before intervention, 1 after)" using different types of impacts, that is, not only trying the simple abrupt permanent impact (yt = w It ) with the xreg option but also trying with a gradual permanent impact (yt= d * yt-1 + w * It ), following the filosophy of Box and Tiao

Hi, I am analyzing a repeated-measures Greco-Latin Square with the aov command. I am using aov to calculate the MSs and then picking by hand the appropriate neumerator and denominator terms for the F tests. The data are the following: responseFinger mapping.code Subject.n index middle ring little ---------------------------------------------------------------------------- 1 1

Hello everyone, I am working for a few days already on a basic algorithm, very common in applied agronomy, that aims to determine the degree-days necessary for a given individual to reach a given growth stade. The algorithm (and context) is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and so I implemented my function in R as follows: DD <- function(Tmin, Tmax, Tseuil,

Full_Name: Robin Hankin Version: 2.4.0 RC OS: MacOSX 10.4.7 Submission from: (NULL) (139.166.242.29) The first cut line described in Trig.Rd for asin() is incorrect in the ascii version of the manpage. The Rd file reads: For \code{asin()} and \code{acos()}, there are two cuts, both along the real axis: \eqn{\left(-\infty, -1\right]}{\(-Inf, 1\]} and Note the inconsistency between the

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

Hi users I'm student who is struggling with basic R programming. Would you please help me with this problem. "My english is bad" I hope that my question is clear: I have a matrix in wich there are two colmns( yp, yt) Yp: predicted values from my model. yt: true values ( my dependante variable y is a categorical;3 modalities (0,1,2) I don't know how to procede to calculate the

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Dear R users, I still feel new to R so please apologize if I am doing something stupid here. My use of the polygon() function produces a result that I cannot comprehend: In a plot, I would like to shade the area below a normal distribution. However, I do not want the entire area to be shaded, but just the area on the right side of a vertical line that I draw through the distribution (in

Hello all, * * I'm having some difficulty, and I think the problem is with how I'm using append() nested inside a for loop. The data are: y,x 237537.61,873 5007.148438,227 17705.77306,400 12396.64369,427 228703.4021,1173 350181.9752,1538 59967.79376,630 140322.7774,710 42650.07251,630 5382.858702,264 34405.82429,637 92261.34614,980 144927.1713,1094 362998.7355,1420 203313.6442,1070

Hi, I am trying to do a power calculation for a difference in proportions test where I want to estimate the sample size required. I know (well estimate) that group one (n1) is 10% of the population and group 2 (n2) is 90% of the population. I know the effect size (h). pwr.2p2n.test only allows one variable to be left null whereas I would like both n1 and n2 to be determined where I know there

Dear R users, i am using locfit package developed by loader in R software, my problem is that as i am doing independont forecast using locfit object , i am able to do independont forecast for more than one years simultaniously. But when i am doing one year forecast(single) this code is giving following error... "Warning message: 'newdata' had 1 rows but variable(s) found have 24