similar to: Peoblem with nls and try

Hi R experts, I'm trying to use nls() for a piecewise linear regression with the first slope constrained to 0. There are 10 data points and when it does converge the second slope is almost always over estimated for some reason. I have many sets of these 10-point datasets that I need to do. The following segment of code is an example, and sorry for the overly precise numbers, they are just

Dear All I would like to use filled.contour to plot something with arrows on it. I did it in this way: filled.contour(1:nx,1:nz,u,col=gray(rev((0:20/20)))) for (j in zseq ) for (i in xseq) arrows(i, j, i+u[i,j],j+w[i,j],length=angleng,angle=angarrow,code=2, lwd=1,col="black") The peoblem is that the arrows use the whole device area, including the key on the right hand side of the

Hello everyone, I have a peoblem to create the twoways effect in the plm package. when i try to create the following dsn1<-plm(lnQ~lnC+lnL+lnM+lnE+eco+RD,data=newdata,effect="twoways",model="within") i have this error: Error in rep.int(c(1, numeric(n)), n - 1L) : negative length vectors are not allowed and to be honest i have no idea what does it mean!! can someone

Hi All, We have installed CentOS 5.3 x86_64 in an HP DL585 server with AMD Opteron 64 bit processor and 16 GB RAM. The kernel version is 2.6.18-128.el5 . Now this has thrown an error message in /var/log/message, Jul 3 21:41:11 db1 kernel: EDAC k8 MC0: general bus error: participating processor(local node origin), time-out(no timeout) memory transaction type(generic read), mem or i/o(mem

I'm currently working with some time series data with the xts package, and would like to generate a forecast 12 periods into the future. There are limited observations, so I am unable to use an ARIMA model for the forecast. Here's the regression setup, after converting everything from zoo objects to vectors. hire.total.lag1 <- lag(hire.total, lag=-1, na.pad=TRUE) lm.model <-

Hi list Maybe someone can help with the following problem (thanks in advance): I need to analisy a long list of data time \fluoscence I want to make one plot with standard deviation and the average data... Could you suggest me how to make that.. The data have this distribution: How can read and extrapolate this data? pippo.csv ps <- read.table(pippo.csv) time fluorescence 0; 0 4.013; 62.96

My situation is this: i have gecko installed using wintricks but when i play metin2 online(i dont a small description before starting the game) or counter strike(when chosen a team - the map description does not appear) and in the console i keep getting the following lines : Code: 0[714ce08]: nsNativeModuleLoader::LoadModule("c:\\windows\\gecko\\0.9.1\\wine_gecko\nssckbi.dll") -

Hi all, I have run a ridge regression as follows: reg=lm.ridge(final$l~final$lag1+final$lag2+final$g+final$g+final$u, lambda=seq(0,10,0.01)) Then I enter : select(reg) and it returns: modified HKB estimator is 19.3409 modified L-W estimator is 36.18617 smallest value of GCV at 10 I think it means that it is

Full_Name: Ben Cooper Version: 1.5.0 OS: linux Submission from: (NULL) (134.174.187.90) The help page for glm.nb (in MASS package) says that it takes "Any other arguments for the glm() function except family" One such argument is start "starting values for the parameters in the linear predictor." However, when called with starting values glm.nb returns: Error in

Dear all, I have weekly data by city (variable citycode). I would like to take the average of the previous two, three, four weeks (without the current week) of the variable called value. This is what I have tried to compute the average of the two previous weeks; df = df %>% mutate(value.lag1 = lag(value, n = 1)) %>% mutate(value .2.previous = rollapply(data = value.lag1,

Hello, I have a question on unit root test with urca toolbox. First, to run a unit root test with lags selected by BIC, I type: > CPILD4UR<-ur.df(x1$CPILD4[5:nr1], type ="drift", lags=12, selectlags ="BIC") > summary(CPILD4UR) The results indicate that the optimal lags selected by BIC is 4. Then I run the same unit root test with drift and 4 lags:

Hi all, I have run a ridge regression as follows: reg=lm.ridge(final$l~final$lag1+final$lag2+final$g+final$u, lambda=seq(0,10,0.01)) Then I enter : select(reg) and it returns: modified HKB estimator is 19.3409 modified L-W estimator is 36.18617 smallest value of GCV at 10 I think it means that it is advisable to

Hi, I was wondering if there is a more efficient way of handling the following method of creating a lagged value in a data frame without using the recursive 'for(i in 1:n)' loop and without using as.ts #Steps to creating a lag variable in a data frame 'my.dat.fr' # with 275 columns, 2400 rows of numbers and factors . The #variable x is a factor of #with five different levels the

Hello all, I need to figure out a way to lag a variable in by a number of days without using the zoo package. I need to use a remote R connection that doesn't have the zoo package installed and is unwilling to do so. So that is, I want a function where I can specify the number of days to lag a variable against a Date formatted column. That is relatively easy to do. The problem arises when I

Hello I'm only user of R and have many little knowledge in programming but I permit to send you some whishes/suggestions for R. which.min like which(), which.min() should also include an argument arr.ind. Note that one can have it with which(a==min(a), arr.ind=TRUE) but if there is a reason to build a special function which.min, why not add also this nice argument? lag() If one wants to

Hello guys .. I would like to have some help about as.table . I made a table with the autocorrelations of the returns whit 10 lags and i get this : autocorrelazione2 <- as.table(c((cor(r2[-1151,],lag(r2))),(cor(r2[- c(1151,1150),],lag(r2, k=2))),(cor(r2[- c(1151,1150,1149),],lag(r2, k=3))),(cor(r2[- c(1151,1150,1149,1148),],lag(r2, k=4))),(cor(r2[- c(1151,1150,1149,1148,1147),],lag(r2,

Suppose we observe N individuals, for each of which we have a time-series. How do we correctly create a lagged value of the time-series variable? As an example, suppose I create: A <- data.frame(year=rep(c(1980:1984),3), person= factor(sort(rep(1:3,5))), wage=c(rnorm(15))) > A year person wage 1 1980 1 0.17923212 2 1981

Hi, I have a problem in fitting GPD distribution. i generate random numbers from gpd distribution from specific parameters using pot packege then i used fitgpd function to estimete the parameters.The estimated parameters are not matched with the given parameters i.e.from which i generate random numbers.I think estimated parameters should be matched with the given parameters.Also suggest me

Hi, how to estimate a the following model in R: y(t)=beta0+beta1*x1(t)+beta2*x2(t)+...+beta5*x5(t)+beta6*y(t-1)+beta7*y(t-2)+beta8*y(t-3) 1) using "lm" : dates &lt;- as.Date(data.df[,1]) selection&lt;-which(dates&gt;=as.Date("1986-1-1") &amp; dates&lt;=as.Date("2007-12-31")) dep &lt;- ts(data.df[selection,c("dep")]) indep.ret1

I am sure that this sort of thing has been asked and answered before, so in case my suggestions don't work for you, just search the archives a bit more. I am also sure that it can be handled directly by numerous functions in numerous packages, e.g. via time series methods or by calculating running means of suitably shifted series. However, as it seems to be a straightforward task, I'll