similar to: Question on ARIMA Prediction

i am using sarima() function as below ___________________________________________________________________________________________ sarima=function(data,p,d,q,P=0,D=0,Q=0,S=-1,tol=.001){ n=length(data) constant=1:n xmean=matrix(1,n,1) if (d>0 & D>0) fitit=arima(data, order=c(p,d,q), seasonal=list(order=c(P,D,Q), period=S),

Can someone please explain what the $minimum result of the optimize function actually is? I'm trying to optimize the function: fitIT<-function(ampFac,ts_wave1,ts_template){ template<-stretchWaveTime(ts_template,ampFac) fit<-calcFit(ts_wave1,template) return(fit) } with >optimize(f=fitIT,interval=c(0.5,4),ts_wave1=test.data[,1],ts_template=test.data[,1]) $minimum [1]

hi all i have a function that uses two inputs, say xdata and ydata. An example is the following, simple1<-function(xdata,ydata) { ofit<-lm(ydata~xdata) list(ofit) } say i use arbitray number for xdata and ydata such that D = x1 x2 y 1 1 10 2 6 6 3 10 7 x<-D[,1:2] and y<-D[,3] if one uses these inputs and rund the program we get the following: >simple(xdata=x,ydata=y)

Hi R-experts, I want to use the jackknife function from the bootstrap package onto a linear model. I can't figure out how to do that. The manual says the following: # To jackknife functions of more complex data structures, # write theta so that its argument x # is the set of observation numbers # and simply pass as data to jackknife the vector 1,2,..n. # For example, to jackknife #

Hola, buenas tardes estoy intentando hacer un bootstrap de un modelo, pero me da el siguiente error: "Error in FUN(newX[, i], ...) : unused argument(s) (list(age = c(33, 47, 49, 56, 60, 64, 64, 66, 68, 69, 71, 71, 72, 73, 74, 75, 75, 76, 78, 81, 83, 83, 36, 43, 46, 47, 49, 49, 51, 51, 52, 52, 53, 54, 54, 54, 55, 56, 56, 57, 57, 58, 58, 58, 58, 59, 59, 60, 61, 62, 63, 64, 65, 65, 66, 66,

Hi all, I try to write a simple function in a script. The script is as follows yo<-function(Xdata) { n<-length(Xdata[,1]) Lgm<-nls(formula=LgmFormula, data=Xdata, start=list(a=1500,b=0.1),weights=Xdata$Qe) return(Lgm) } After the execution of the script, when I call the function yo on data called NC60.DATA I get an error. #yo(NC60.DATA) Erreur dans eval(expr, envir, enclos)

Hi, I am parsing a C++ file using cindex.py and want to get the template parameters to a specific node. However, the tree seems to be different depending on if the template parameter is a struct/class or a simple type such as int or float. In the first case the template type is appended as a child to the VAR_DECL node (the TYPE_REF node seen in the example below), but this is not the case with

I have a set of data in the form x1, y1, z1 x1, y2, z2 ... x1, yN, zN x2, y1, z(N+1) x2, y2, z(N+2) ... x2, yN, z(2N) ...and so on... xM, yN, val(M*N) I have been trying to figure out how to get R to use this data in a persp plot. So far the only thing that I can figure out to do is to break the data file into three different files. The first file contains the x-coordinate data: x1 x2

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Hi, I have been using R for over a year now. I am a very happy user. Thank you for making this happen. This is my first question to this list. I trying to add some functions to quantmod that would enable me to draw arbitrary lines and text and make sure they are redrawn. I have created following function: require(quantmod) # Add horizontal line to graph produced by quantmod::chart_Series()

Hello R-Users,   I have one binary dependent variable and a set of independent variables (glm(formula,…,family=”binomial”) ) and I am using the function stepAIC (“MASS”) for choosing an optimal model. However I am not sure if stepAIC considers significance properties like Likelihood ratio test and Wald test (see example below).     > y <- rbinom(30,1,0.4) > x1 <- rnorm(30) > x2

Hello all, I have been using R for about 3 weeks and I am frustrated by a problem. I have read R in a nutshell, scoured the internet for help but I either am not understanding examples or am missing something completely basic. Here is the problem: I want to plot data that contains dates on the x axis. Then I want to fit a line to the data. I have been unable to do it. This is an example of

Airon, I used R2.4.0 on a Windows XP (SP2) (not Chinese :-)) and it still works: > data = read.csv("u:/airon.csv") > xdata = data$Adj..Close > modwt.la8 = modwt(xdata, "la8", n.level=6) > summary(modwt.la8) Length Class Mode d1 1467 -none- numeric d2 1467 -none- numeric d3 1467 -none- numeric d4 1467 -none- numeric d5 1467 -none- numeric d6 1467

I looked through the documentation and the mailing lists and could not find an answer to this. My apologies if it has already been answered. If it has, a pointer to the relevant discussion would be greatly appreciated. Creating S4 classes containing environments exhibits unexpected behavior/features.? These have a different in two ways: 1) slotName for the data: ".xData" instead of

Greg, Two thoughts: 1. It might be possible that 'vars' is a reserved word of sorts and if you change the name of your vector RF might be happier 2. A way that works for me is to call importance as follows: sel.imp <- importance(sel.rf, class=NULL, scale=TRUE, type=NULL) and then use the 'names' of the imp data frame to be absolutely clear to RF you are talking about the

Hi list, is there a way to define some kind of private Variable? I would like to prevent the user from manipulating fields on his own, in order to not destroy data structures. The problem is, that as soon as the variable exists in the environment it is accessible via t$secret_value. test <- setRefClass("test", fields=list( secret = function(value){ cat("the function was

How can I remove columns with NaN entries ? Here is my simple example: > data <- read.csv("test.csv") > xdata <- data[3:length(data)] > xs <- lapply(xdata, function(x){(x - mean(x))/sqrt(var(x))}) > x <- data.frame(xs) > x C D E F 1 -0.7071068 NaN -0.7071068 -0.7071068 2 0.7071068 NaN 0.7071068 0.7071068

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Hi all, After an upgrade from R_2.10.1 to R_2.11.1 I am now getting the following error: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? This occurs in the initialize method of S4 classes where I was initialising attributes eg: .Object[['realtimeState']] <- list() I can avoid this new error by altering the code to do: .Object$realtimeState <-

Hi: I have encountered problems with imodwt and universal.thresh.modwt and cannot find any reference in R Search. Hope someone can give me some ideas: Starting with modwt.la8 <- modwt(xdata, "la8", n.level=6) <-- this seems to work fine (1) ydata <- imodwt(modwt.la8) will always give ydata as numeric(0) (no values) instead of being a time series data with