search for: univari

How to test the statistical significance of the difference of two univariate Linear Regression betas? Hi all, There are two samples of data: D1 and D2. On data D1 we do a univariate Linear Regression and get the coefficient beta1. On data D2 we do a univariate Linear Regression and get the coefficient beta2. How do I test the statistical significance of (beta1-beta2...

Hey, Does anyone know of a package in R that provides univariate kernel density estimation with boundary correction ? or how to easily extend an existing bivariate kernel density estimation function (e.g. lambdahat in the spatialkernel package) with boundary corrections to allow univariate density estimation? Thanks a lot, Steve B. -- View this message...

Dear R users, I use the excelent Anova function of the library car because the easy way to get sphericity correction. Unless I use the scan function. I have not been able to access the values ​​of sum squares and degrees of freedom for each effect in the univariate summary table. Example of the car library for Anova function: library(car) phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)), levels=c("pretest", "posttest", "followup")) hour <- ordered(rep...

This seems like a FAQ, but I can't figure it out. I have a mv ts object: R > tsp(pg) [1] 1982 2003 1 R > dim(pg) [1] 22 12 and a univariate ts: R > tsp(rw) [1] 1690 1996 1 Yet, when I try to intersect them: R > tsp(ts.intersect(rw, pg)) [1] 1982 2176 1 the process goes awry. How to I get rw and pg to be one ts that runs from 1982 to 1996 and has 13 univariate time series in it. Any help appreciated. -Andy R > v...

Hello! I want to realise an univariate time series analysis in R, can someone help me for the first steps? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Univariate-Time-Series-Analysis-in-R-tp4638538.html Sent from the R help mailing list archive at Nabble.com.

...In checking a function I am adding to an R package, I get the following warning pair: ... Bad \usage lines found in documentation object 'nominal': "\\method{print}{nominal}"(x, max.print = 10, posthoc = "std.pearson.residuals.sign", assoc = ifelse("univariate" list(c("N", "alpha.X2", "uc.12", "uc.21")), list(c("N1", "N2", "N12", "uc.12", "uc.21"))), sort.key = NULL, ...) "\\method{summary}{nominal}"(object, posthoc = &quot...

...lpers, 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! => The problem is probably that this time series has to much noise so that it consequently gives the following error. > plot(stl(Timeserie)) Error in stl(Timeserie) : only univariate series are allowed. I also...

Hi the list *** New package *** R to LaTeX : Univariate analyses r2lUniv *URL:*http://www.r-project.org, http://christophe.genolini.free.fr/r2lUniv *** Description *** r2lUniv performs some basic analyses, then generates a code to be included in a LaTeX document to print the analyses in a (so nice!) LaTeX way. r2lUniv performs the analyses automati...

Hi the list *** New package *** R to LaTeX : Univariate analyses r2lUniv *URL:*http://www.r-project.org, http://christophe.genolini.free.fr/r2lUniv *** Description *** r2lUniv performs some basic analyses, then generates a code to be included in a LaTeX document to print the analyses in a (so nice!) LaTeX way. r2lUniv performs the analyses automati...

Hi, Does anyone know if R has a Lagrange multiplier (LM) test for ARCH effects for univariant time series? Thanks! -- Tom [[alternative HTML version deleted]]

hi everyone! i want to check the autocorrelation function for a univariate time series (streamflow) in a data frame as below: < DF <- read.table("D:/file path....") < DF year jan feb mar apr ...... dec 1966 0.504 0.406 0.740 0.241 0.429 1967 0.683 0.529 0.780 0.443 0.503 . . . . what i first tried...

Hallo everyone I have two univariate time series (class ts) describing the same variable. They have the same resolution, but span different periods in time with a big gap in between. I need to append one to the other such that they are one object, with the gap filled with NAs. The method ts.union produces a multivariate time series...

Hello, I have a concrete statistical question: I have a sample of an univariate mixture of an unknown number (k) of normal distributions, each time with an unknown mean `m_i' and a standard deviation `k * m_i', where k is known factor constant for all the normal distributions. (The `i' is a subscript.) Is there a function in R that can estimate the number of...

This is a cryptographically signed message in MIME format. --------------ms010908060700000604050108 Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit Sorry. You're right about the univariate numeric operators. My bad. However, I was expecting !x to return a time series, just like the binary logical operators do. For example: > b <- ts(1:10) > 5 > b Time Series: Start = 1 End = 10 Frequency = 1 [1] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE > b...

Hi, I got the same problem like http://tolstoy.newcastle.edu.au/R/devel/04/11/1204.html R crashes when I use the em function from the mclust package on univariate data and on a special case on bivariate data (when the matrix is not provided as written in the manual). It seems as if the problem is the format of the data to be analyzed. Operating System: Windows XP (SP2) R version: R-2.0.1 The following example causes a crash of R: # univariate example...

.... I define it in the following way: *u<-read.csv("C:/CELEBREX.csv",header = TRUE) u.ts<-ts(u, start=c(2005,9), frequency=12) * The issue is that when I try to use stl(u.ts, 'per') Then the following error message is displayed: *Error en stl(u.ts, "per") : only univariate series are allowed * I know that stl needs a univariate time series in order to run, but I've already defined it in *u.ts. *Moreover, if I use the same *u.ts* with functions which also requires univariate time series, i. e. *auto.arima(u.ts, d=1, D=1)* Series: u.ts ARIMA(0,1,0)(0,1,1)[12...

In ggplot2, I would like to make a boxplot that has the following properties: (1) Contrary to default, the meaningful axis should be the horizontal axis. Lattice does this, for instance, by library(lattice);bwplot(~mtcars$mpg) (2) It is *univariate*, i.e., of a single vector, say mtcars$mpg. I do not wish to make separate plots for the different values of mtcars$cyl. (3) Nothing on the meaningless axis--the axis that does not correspond to values of mtcars$mpg, the axis which by default is horizontal--should suggest a scale. Thus, there...

...am interested in a applying wavelets as a smoothing tool for my (1-dimensional) data. I looked into wavetresh and waveslim packages but could not quite figure out an obvious way to do this after running dwt or wt functions. Would someone be able to point me in the right direction on how to denoise univariate data using one of wavelet packages available in R? Thank you very much Jane ps kalman filter does a good job on my data but tends to dampen spikes too much so i was looking to compare its performance with wavelets denoising. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

Hi, I am trying to use the stl function in the ts package. It requires that the data is a univariant time series at the moment my data is in a vector. I have coerced it to a time series using.... crimets <- ts(crimeData) However, this does not work. Does anyone have any suggestions? Cheers, Sam. p.s. I am fairly new to R so apologies if this is a stupid posting.

just a short beg for the next R 2.3 version: I know it is easy to add the sd into summary() in the source bowels of R---but everytime R is updated, my change disappears. :-(. I do not believe that R has an easy extension mechanism for univariate summaries, short of a function rewrite here. Could this please be added into R 2.3? Aside, a logical ordering might also be: mean sd min q1 med q3 max rather than have mean buried in between order statistics. regards, /iaw