similar to: Fry Plots

I am having a hard time putting the below into a loop, where it pulls out ppt from all he stations I have versus having to go through and hard code the data to the specific stations. I tried stnID <- stnid[which(duplicated(stnid)==FALSE)] for(i in 1:length(stnID)) { ppt[i] <- ppt[which(stnid==[i])] } but it doesn't like to use the which function inside a for loop? Any idea's here is

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

Hello All, When I use bw.SJ (based on Sheather & Jones, 1991) in R to estimate the bandwidth for a highly skewed data, I get the following message: "sample is too sparse to find TD". I played around with the parameters such as no. of bins (nb), lower, upper (range over which to minimize) to no avail. My sample size is 50,000. Can anyone tell me what this means and of some

Dear all, I created a n*2 matrix and I want to replace the ith row with a vector. Can anyone suggest me what is the simple way to do it? Sorry for bothering you with such simple question. I appreciate any hints or advice. Thanks in advance. Cassie [[alternative HTML version deleted]]

Dear all, I am trying to simulate from truncated Pareto distribution. I know there is a package called PtProcess for Pareto distribution...but it is not for truncated one. Can anyone please help me with this? Thanks in advance. Cassie [[alternative HTML version deleted]]

Hello, I am using the lmomco package (lmom.ub and pargev) to compute the GEV parameters (location, scale, and shape), which are used to estimate return values. I was wondering how/if I can calculate upper and lower confidence (CI_u, CI_l) intervals for each return frequency using the GEV parameters to fill-in the table below? Xi (location) = 35.396 Alpha (scale) = 1.726 Kappa (shape) =

Dear all, I am trying to simulate from discrete uniform distribution. But I could not find any in-built code in R. Could anyone help me please? Thanks in advance for the time and help. Cassie [[alternative HTML version deleted]]

Dear all, I have a data set which has latitude, longitude (not in increasing order) and observed precipitation corresponding to those locations. I am using image.plot command for that. But I want to overlay a map of US on that plot. I know we can use map('usa') to draw it, but I dont know how can I overlay it on the plot of the precipitation data. Can anyone please help me with it?

Dear all, I am trying to define an array as follows: a=array(NA,c(m,2,N,G)), Even though the numbers N and G are fixed, m is a vector. So, I can't define 'a' as above. For eg, N=3 G=6, but m=c(2,7,5) and length(m)=N. Can anyone suggest me how can I define 'a' when m is a vector? Thanks in advance for your help. Cassie [[alternative HTML version deleted]]

Hola a todos, Estoy utilizando la libreria e1071 para clasificar unos datos. Me gustaría poder guardar los modelos en el disco duro y no en memoria de R. He visto que hay una función: save : que guarda el modelo en memoria y load: que carga ese modelo Ejemplo: #saving the best model save(calibrate.rf.model1, file=''bestmodel.rda'') #loading the best model

Hello everyone I hope Im not bothering you all again. I have just begun to use R and so Im not yet familiarized with it.. I ve got an assignment which consists in calculating the area of a circle given a certain radius and center using the monte carlo method, which means that I have to plot a circle given its parameters. Limit the area inside it...with as many sample points as possible...and

Dear all, I need to simulate values from a Poisson distribution which is truncated at certain value 'a'. Can anyone tell me if there is in-built package in R which can simulate from a truncated Poisson? If not, what should be the steps to write a function which would do that? Thanks in advance. Cassie [[alternative HTML version deleted]]

Hi all, I have a matrix which looks like the following, x=matrix(c(1,2,3,4,3,5,4,6,4,9),5,2,byrow=T) Now, I want to replace the 2nd columns of those 4 rows which have duplicate entries in the 1st column. For example, x[2,1]=x[3,1]=3 and I want to replace x[3,2] by x[2,2]. Similarly, I want to replace x[5,2] with x[4,2], which means that for duplicate entries in the 1st column, I want to replace

Hello everyone, I am wondering if there is any routine in R which can convert time given in 'seconds' unit to the 12 hour time format. For example, suppose the data set looks like x=c(36885,84000,20) #x in seconds I want to get the output as [1] " 11:14:45 AM" [2] " 11:20:00 PM" [3] "12:20:00 AM" Does anyone have any idea? Thanks in advance. Cassie

Hello R-users, I am having a problem with the 'break' command in R. I am wondering if anyone can help me out with this. My program is similar to the following. a=rep(NA,5) a[1]=0 for(i in 2:5) { a[i]=a[i-1]+runif(1,0,3) if(a[i]>5) { i=2 break } } What exactly I am trying to do is find the sequence 'a' where the individual values of 'a'

Hello R-users, I am trying to do an image plot where I have been given latitudes, longitudes and the values at the corresponding locations. A sample of the data is given as follows: values=c(0,1,0,0,0,0,2,2,0,0) lat=c(29.6660,29.6756,29.3492,29.2654,29.2827,29.4070,35.3510,35.6590,35.7587,38.2794)

Dear all, I am trying to plot 3 histograms on the same graph using the following command. hist(x,xlim=c(0,100)) hist(y,add=TRUE) hist(z,add=TRUE) The xlim of y is c(20,21) and that of z is c(99,99.5) , whereas the variable x has xlim at c(0.5,2). Apparently, the graph end of displaying a line only, corresponding to each histogram due to the wide range of the xlim and tightness of the

Hi everyone, I have bunch of date and time observations in the format %Y-%m-%d %I %M %S %p. I used strptime() to read this format. But the problem is some of the times are in the format of %I %M %p, so for those times, strptime is giving me NA values. For example, strptime(paste("2009-04-08","1:49:47 PM"),format="%Y-%m-%d %I:%M:%S %p") [1] "2009-04-08

Context: I'm relatively new to R and am working with very large datasets. General problem: If working on a dataset requires that I produce more than two objects of roughly the size of the dataset, R quickly uses up its available memory and slows to a virtual halt. My tentative solution: To save and remove objects as they're created, and load them when I need them. To do this I'm

Dear all, I am struggling to understand the johansen test procedure in the context of co-integration in time series. Yes I understand that this forum is not directly statistics related but still I am posting here hoping that I would get som help. The error correction representation of a VAR[p] model can be written as: Delta y[t] = A[0]*y[t-1] + A[1]*Delta y[t-1] +..............