search for: irregularities

Hello all, I'm sorry if my question seems basic. Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain the following relation with my variables : (Yes,No)~ ?0 + Age We note this this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . After that we calculated : model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) summary(model1)

Dear Lenny, You can do this by using Age as an offset factor. dataset$wAge <- dataset$Age * 1.02 glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data = dataset) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie &

Dear Thierry, Thanks a lot for this answer, I mean i want to obtain such model *Behavior1 = ?0+?1*Age* , the purpose is to obtain *?1*. I want to be sure that the odds value could be the ?1. Or how to calculate it ? Thanks again for your precious help. Lenny <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>

Hi all, Issue: I have two datasets, one is a regular time series (rain gauge) with resolution of 10 minutes. The other one is an irregular time series (link). Now I want to analyze the correlation between these two datasets with linear regression. The regular time series is a data.frame and the irregular time series is a zoo object. Problem: For the irregular time series (link) I want also a 10

Dear colleagues, particularly academic ones, So I'm creating a Microsoft Word template for myself so that every time I teach a new course, I don't have to enter in the dates manually for each class session. I'd like to use an R script that can generate an irregular series of dates starting from one date (semester begin) to another (semester end) using an irregular interval in

I built some reasonably successful tools in a graphical database for reconstructing the developmental turning points for feedback loop driven natural processes. I'm trying to move it to R and am having difficulty with the very basics, i.e. a) defining time series using time as a natural number rather than a place in a table. I was also hoping b) someone might have built some of the

Dear R users I am currently investigating time series analysis using an irregular time series. Our study is looking at vegetation change in areas of alien vegetation growth after clearing events. The irregular time series is sourced from Landsat ETM+ data, over a six year period I have 38 scenes. For certain periods I have monthly data while for others, images are up to three months apart. So far

I have uploaded to CRAN a new package named 'its' (Irregular Time-Series). It implements irregular time-series as an S4 class, extending the matrix class, and records the time-stamp of each row in the matrix using POSIX. Print, plot, extraction, append, and related functionality are available. Feedback and suggestions are welcome. Giles Heywood

I have uploaded to CRAN a new package named 'its' (Irregular Time-Series). It implements irregular time-series as an S4 class, extending the matrix class, and records the time-stamp of each row in the matrix using POSIX. Print, plot, extraction, append, and related functionality are available. Feedback and suggestions are welcome. Giles Heywood

Background: OS: Linux Mandrake 9.1 release: R 1.9.0 editor: Xemacs 21.4 frontend: ESS 5.1.23 --------------------------------- Colleagues I have two time series (upwelling index and water temperature) of evenly spaced, daily data over 18 months, but the upwelling index series has a gap of about 2 months right in the middle of it. I want to do the acf, pacf, ccf, and a cross-spectral analysis

I make quite a lot of use of irregular time-series, and had already spent a bit of time writing an 'its' class when the 'irts' class was released via the package 'tseries'. I have experimented with the 'irts' class, and have some practical issues with its use. In some applications of irregular time-series (in my case these are financial and econometric) there are

Hi all, Issue: I merged two zoo objects (a regular and an irregular). After the merge I used the function 'na.approx' to have also values in the resolution of the regular time series. Problem: After approximation some rows at the beginning or at the end of the zoo objects disappear due to the 'na.approx' algorithm. Now I just want to have all the rows of the regular time series

Hello, I am having trouble constructing a time series object for my data. This is because the frequency is irregular: one year, there may be only 100 individuals, another 200. There are 100 measurements for every individual. I have the observations in a data frame with the year that they were taken from as a factor. I would like to plot the top 10 mean measurements for each year and connect them

Dear R developpers, I am a user of Splus since many years and I have developped lots of functions to plot graph of data and model results of irregular or regular times series. In Splus regular times series are created using the rts function and irregular time series using the its functions. In both cases, times is given as a numeric vector. There is no problem in plotting a regular and an

Hi, I realized that when I have irregular series to feed into lineChart, the interval of each point in the chart does not seem to take care of irregular time interval I specified in my input xts time series. But rather, lineChart seems to take each point as equal spaced time series. For example, I have the following code: library(quantmod) options(digits.sec=3) t0 <-

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

A new version of tseries (0.9-10) has been uploaded to CRAN. The new version contains the class "irts" for irregularly spaced time series. Irregular time series are basically time series where each observation (uni- or multivariate) has a time-stamp represented by an object of class "POSIXct". It provides some basic functionality such as reading and writing irregular time

Hi, I am trying to read the following type of data from a .csv file to form an irregular time series object. I want to use it with the VaR package. How do I read it in correctly to an irregular time series object? Anupam. date,Open,High,Low,Close,Volume,OpenInterest,Contract 1972-08-16,54.25,54.25,54.25,54.25,1,1,KC1973H 1972-08-17,54.25,54.25,54.25,54.25,0,1,KC1973H

Given a set of coordinates that form an irregular sampling area, is there an R function to determine boundary points (coordinates defining the limits of the area), either with or without user interaction ? # for example, given the following irregular sampling area, how could I define the boundary polygon? library(SemiPar) data(scallop) plot(scallop$longitude, scallop$latitude) Thanks. --Dale

Dear All, I could not find the irregular forms table in xapian. Please, could you tell me how to define/add words to the irregular forms table in xapian? Thank you a lot. Sascha