similar to: Box Cox parameter for time series

Hello everybody! I have a list of length 5000 whose components are (mostly) "ts" objects, but some these components are intentionally left empty, ie, they are "NULL" components of the list. My question is how can I get the position of these null components in a effective way (I'm trying to avoid a for-if rutine). Thanks!!! [[alternative HTML version deleted]]

Hello R experts! Last week I run in to a lot a problems triyng to fit an ARIMA model to a time series. The problem is that the internal process of the arima function call function "optim" to estimate the model parameters, so far so good... but my data presents a problem with the default method "BFGS" of the optim function, the output error looks like this: Error en

dear members, I have a heteroscedastic time series which I want to transform to make it homoscedastic by a box cox transformation. I am using Otexts by RJ hyndman and George Athanopolous as my textbook. They discuss transformation and also say the fpp3 and the fable package automatically back transforms the point forecast. they also discuss the process which I find to be

Hello everybody! I have an ARIMA model for a time series. This model was obtained through an auto.arima function. The resulting model is a ARIMA(2,1,4)(2,0,1)[12] with drift (my time series has monthly data). Then I perform a 12-step ahead forecast to the cited model... so far so good... but when I look the plot of my forecast I see that the result is really far from the behavior of my time

Dear Rlist, Using an example in box.cox.powers() help, I have the following warning message. example: library(car) >attach(Prestige) > box.cox.powers(income) Box-Cox Transformation to Normality Est.Power Std.Err. Wald(Power=0) Wald(Power=1) 0.1793 0.1108 1.6179 -7.4062 L.R. test, power = 0: 2.7103 df = 1 p = 0.0997 L.R. test, power = 1: 47.261 df = 1 p = 0

Hello I am using box.cox() and I get this error message: Warning message: 'box.cox' is deprecated. Use 'bcPower' instead. See help("Deprecated") and help("car-deprecated"). I went to help but I did not understand the explanation, I am still wondering what is really happening. Thanks /R

Dear experts, I tried to learn about Box-Cox-transformation but found the following thing: When I had to add a constant to make all values of the original variable positive, I found that the lambda estimates (box.cox.powers-function) differed dramatically depending on the specific constant chosen. In addition, the correlation between the transformed variable and the original were not 1 (as I

Hi: Recently, I want to perform a transformation on my data to make it more normal, meanwhile the order statistics is unchanged. So I decided to use a box-cox transformation. below is the qq-plot of the original data http://n4.nabble.com/file/n1011015/start%2Bvalue%2Bproblem%2B02.jpeg Note that the min of my data is -1099, so I add a fix value 1200 to the original sample. I choose the

Hi all: I am trying to use the BiodiversityR package in Rcommander since I need to box-cox transform some data. However, even when trying with the example files, I get this error just after selecting the box cox transformation in the Menu, and Rcommander and Rstudio just shut down. What is it? What could I do? Thanks a lot The instruction at "0x00000001" referenced memory at

Hi out there Is there a way to get the estimated coefficients in a logistic / Cox regression without having to specify a 'formula' but by only giving the model matrix? Example for Cox regression: ## predictors n <- 50 q1 <- rnorm(n) q2 <- rgamma(n, 2, 2) Z <- cbind(q1, q2) ## response ttf <- rexp(n) tf <- round(runif(n)) ## compute estimates res <- coxph(Surv(ttf,

Dear r-help members I posted this message already yesterday, but don't know whether it reached you since I joined the group only yesterday. I would like to estimate the boxcox transformed model (y^t - 1)/t ~ b0 + b1 * x. Unfortunately, R returns with an error message when I try to perform this with the call nls( I((y^t - 1)/t) ~ I(b0 + b1*x), start = c(t=1,b0=0,b1=0), data = mydataframe)

Hi,   Could any one please help how I can transform data based on Box-Cox Transformations in R.   Any helps will be much appreciated.   thanks, Kagba [[alternative HTML version deleted]]

Hi all, Does anyone know of a function that return the best lambda in box-cox transformation? many thanks for any help. -- Cristiane S. Rocha Laboratorio Genoma Funcional - Bioinform?tica Centro de Biologia Molecular e Engenharia Genetica Universidade Estadual de Campinas Campinas - SP - Brasil Tel:(19)3788-1119

Hello! This is my first post to the help list; I have been using R only for a couple of months. I have been able to find answers to most questions through the archives, but I have not seen any posts about double sided Box-Cox models. Is there any way to run do this in R? Thanks, --Bill West [[alternative HTML version deleted]]

Dear all R users, I have a dataset 'data' and I want to see the effect of Box-Cox transformation on it Interactively for different lambda values. I already got a look on function "vis.boxcoxu" in package "TeachingDemos". But I didn't find any option to put user's own dataset. Can anyone tell me how to put my own dataset here i.e. "data"? Thanks and

Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using

Hello R experts! I'm running a FOR loop in which at every step an arima model is generated. The problem is some series produces numeric problems with optim. My question is if there is a way of telling to R that at every critical error of optim jumps to the next series instead of stopping the calculations. Or better yet, tell it to run another arima fit but with a different optmization

Hi All, I'm analysing some data that is conventionally modelled as log(Y) = a + bX + e. However, using the boxcox function, it appears that the optimum value of lambda is approx 0.05. I have 40 data sets of differing sizes and for about half of these, lambda is significantly non-zero. So, it is worth looking into. The alternative model, Y^lambda = a + bX + e, has been explored before by

Hello, I'm currently trying to model the movement of a slope (v.obs) with a regression model. The data can be found following the given links: either http://www.sendspace.com/file/dnugwc or http://rapidshare.com/files/420569660/sel.day.txt I want to use the Box-Cox transformation to normalize the response as well as the predictor variables. The scatterplot looks like this: library(zoo)

Hi, I wanted to do the cox model using a matrix. The following lines illustrate what I want to do: -------------------------------- dat <- matrix(rnorm(30), ncol=3,dimnames = list(1:10,letters[1:3])) Survival <- rexp(10) Status <- ifelse(runif(10) < .7, 1, 0) mat <- as.data.frame(cbind(dat,Survival,Status)) cmod <- coxph(Surv(Survival, Status) ~ a+b+c, mat)