similar to: Data decomposition

Hi all, I?m fitting GLM?s and I can?t interprete the coefficients when I run a model with interaction terms. When I run the simpliest model there is no problem: Model1<-glm (Fishes ~ Year + I(Year^2) + Kind.Geographic + Kind.Fishers + Zone.2 + Hours + Fishers + Month, family = poisson(log)) # Fishes, Year, Hours, and Fishers are numeric, Kind.Geographic, Kind.Fishers, Zone.2 and

Good morning all! I am attempting to superimpose a moving-average smoother onto a graph of daily plots. These plots (in table[,2] below) span about 350 days and looks very noisy. I'd like for this smoother to plot the average of each group of 7 consecutive days (weekly) and show a line which joins these series of averages. Given the definition of MA, the first and last points will

Dear R-experts, I am struggling with the following problem, and I am looking for advice from more experienced R-users: I have a data frame with 2 identifying variables (comn and mi), and an output variable (x). comn is a variable for a company and mi is a variable for a month. comn<-c("abc", "abc", "abc", "abc", "abc", "abc",

Dear R users, I cannot display ylab with the following code while trying to stack 7 rows of 3 histograms each. Thanks in advance! par(mfrow=c(7,3)) par(mar=c(2,2,2,2)) par(oma=c(5,5,0,0)) with (newdata <- subset(table, Month1 == "1"), hist(newdata$CarapWid, breaks=5*(0:80), col="gray80", main="All individuals", xlab="", xlim =c(15,85), ylab="April

Dear all, My data is by minutes and I can see it has seasonal trend by daily and weekly. How do I decompose the minute data into daily and weekly some data: > dput(tail(dt_train,100))structure(c(11L, 11L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 10L,

Hallo you can extract POSIX object tv <- as.POSIXct(index(dt_train)) and use cut together with aggregate cut(tv, "hour") aggregate(dt_train, list(cut(tv, "hour")), mean) 2014-10-06 21:00:00 9.807692 2014-10-06 22:00:00 8.666667 Cheers. Petr ?t 3. 10. 2024 v 17:25 odes?latel roslinazairimah zakaria < roslinaump at gmail.com> napsal: > Dear all, > > My

A stupid question but I just cannot see how to do this. I have a loop that does some calculations and puts the results in a vector for each iteration, but I cannot see how to get the data out of the loop in such a way that I can use it. I can print it but how do I get it into a set of vectors or what ever. Any help gratefully received. Thanks Example cata <- c( 3,5,6,8,0, NA) catb <-

If I have data (below) and need some help in figuring out how I can change the values of my date column, so that a year will be from September-August? So the year 1990 = September 89-August 90; 1991 = September 90-August 91, etc... I was trying to use the if() function, but am unable to figure it out. I basically need to change the years associated with September-December to the following

I came across the package 'ineq' that computes a variety of inequality measures (e.g. gini, theil etc). I want to compute the Theil index (racial segregation) and decompose the total into sub-components (by geog levels). I think the package doesn't report the decomposition (correct me if I'm wrong). Just wonder is that available elsewhere? K.

I am stuck on a simple problem where an example works fine but the real one does not. I have a data.frame where I wish to sum up some values across the rows and create a new data.frame with some of old data.frame variables and the new summed variable. It works fine in my simple example but I am doing something wrong in the real world. In the real world I am loading a labeled data.frame. The

Dear R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

All, I have been just recently working with zoo objects for trading systems. Can someone please help with these basic questions? Given a daily time series downloaded using get.hist.quote() from the tseries package, ie...... startDate= as.Date("2000-01-01") endDate= as.Date("2011-01-29") frequency= 'd' s= get.hist.quote('IWF', start= startDate, end=

Is there a way of aggregating 'zoo' daily data according to day of week? eg all Thursdays I came across the 'nextfri' function in the documentation but am unsure how to change this so any day of week can be aggregated. I have used POSIX to arrange the data (not as 'zoo' series) according to day of week, but am curious if I've missed if a similar option available

I have a simple data base and I want to produce tables for each variable. I wrote a simple function fn1 <- function(x) {table(x)} where x is a matrix or data.frame. and used apply to produce a list of tables. Example below. How do I apply the colnames from the matrix or names from the data.frame to label the tables in the results in the list. I know that I can do this individually but

Hi all, I have a time series that contains double seasonal components (48 and 336) and I would like to decompose the series into the following time series components (trend, seasonal component 1, seasonal component 2 and irregular component). As far as I know, the STL procedure for decomposing a series in R only allows one seasonal component, so I have tried decomposing the series twice. First,

Hi mailinglist members, I’m actually working on a time series prediction and my current approach is to decompose the series first into a trend, a seasonal component and a remainder. Therefore I’m using the stl() function. But I’m wondering how to get the single components in order to predict the particular fitted series’. This code snippet illustrates my problem: series <-

This is probably a simple problem but I don't see a solution. I have a data.frame with a number of columns where I would like 0 <- NA thus I have df1[,144:157] <- NA if df1[, 144: 157] ==0 and df1[, 190:198] <- NA if df1[, 190:198] ==0 but I cannot figure out a way do this. cata <- c( 1,1,6,1,1,NA) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) dogb <- c(2,4,6,8,10,

Hello R users, Can someone tell if there is a package in R that can do outlier detection that give outputs simiilar to what I got from SAS below. Many thanks in advance for any help! Outlier Details Approx Chi-

Dear R'sians, Would really appreciate if you could suggest a more efficient way to order the columns of a dataset. The column names of the dataset contain indices separated by a period. Following are examples of my code and the dataset. oC <- function(tg=x2) { lth <- length(grep("T",names(tg))) thix <-

Hi, Can anyone please point to how to decompose BCCB (Block-Circulant-Circulant-Block) matrices? I am interested in the derivations: I do know that this can be numerically done using 2-dimensional FFTs. Many thanks and best wishes!