similar to: heteroscedastic bivariate distribution with linear regression - prediction interval

Displaying 20 results from an estimated 4000 matches similar to: "heteroscedastic bivariate distribution with linear regression - prediction interval"

2009 Dec 13
0
How to control the skewness of a heteroscedastic variable?
Dear listusers, I don't know whether my problem is statistical or computational, but I hope I could recieve some help in either case. I'm currently working on a MC-simulation in which I would like to control the skewness of a heteroscedastic dependent variable defined as: y=d*z+sqrt(.5+.5*x^2)*e (eq.1) where d is a parameter and, z, x, and e are gamma r.vs. The variables x
2010 Aug 24
0
Using Splus Bootstrapping to find a confidence interval with a given corrected correlation value of two bivariate variables
Good morning, I am trying to find a S-Plus code which shows how to find a confidence interval using a bootstrapping on a corrected correlation value of a two bivariate variables. If you happen to know one, please shows me. I am greatly appreciated your help. Have a wonderful day, Minh -- View this message in context:
2009 Dec 13
0
How to control the skewness of a heteroscedastic variable? - A Correction
When going through my earlier post I find a mistake in the example that I provided. The correct version is provided below. I also start to suspect that my problem is that although the cumulant of a sum of independent variable is the sum of the cumulants, the moments of a sum is not the sum of the moments. But that might not be the only flaw in my application. Regards, Karl-Oskar #An
2011 Jul 08
1
How to generate heteroscedastic random numbers?
Hello, I have tried to generate numbers randomly which follow normal, Student-t and skewed Student-t distributions. However, when I check those series for heteroscedastisity test (ARCH) results are showing that there is no heteroscedastisity. As we all know, returns (financial returns) usually have heteroscedastisity. My question is, is it possible somehow generate random numbers which have
2023 Aug 31
1
simulating future observations from heteroscedastic fits
Hello, All: I want to simulate future observations from fits to heteroscedastic data. A simple example is as follows: (DF3_2 <- data.frame(y=c(1:3, 10*(1:3)), gp=factor(rep(1:2, e=3)))) # I want to fit 4 models # and simulate future observations from all 4: fit11 <- lm(y~1, DF3_2) fit21 <- lm(y~gp, DF3_2) library(nlme) (fit12 <- lme(y~1, data=DF3_2,
2007 Apr 16
1
Modelling Heteroscedastic Multilevel Models
Dear ListeRs, I am trying to fit a heteroscedastic multilevel model using lmer{lme4- package). Take, for instance, the (fictive) model below. lmer(test.result ~ homework + Sex -1 + (1 | School)) Suppose that I suspect the error terms in the predicted values to differ between men and women (so, on the first level). In order to model this, I want the 'Sex'-variable to be random on
2003 Mar 14
0
gls with "crossed heteroscedasticity"
Dear All, I am using the function gls (in the nlme package) and I would like to fit a heteroscedastic model, with different variances for each of the levels of two stratification variables. In p. 210 of Pinheiro & Bates ("Mixed effects models in S and S-Plus", 2000, Springer), the authors show the use of the "*" operator. However, that is not what I want, because it
2012 Mar 03
2
contour for plotting confidence interval on scatter plot of bivariate normal distribution
Dear all, I created a bivariate normal distribution: set.seed(138813) n<-100 x<-rnorm(n); y<-rnorm(n) and plotted a scatterplot of it: plot(x,y) Now I'd like to add the 2D-standard deviation. I found a thread regarding plotting arbitrary confidence boundaries from Pascal H?nggi http://www.mail-archive.com/r-help at r-project.org/msg24013.html which cites the even older thread
2012 Mar 23
1
Nonparametric bivariate distribution estimation and sampling
Dear all, I have a bivariate dataset from a preliminary study. I want to do two things: (1) estimate the probability density of this bivariate distribution using some nonparametric method (kernel, spline etc); (2) sample a big dataset from this bivariate distribution for a simulation study. Is there any good method or package I can use in R for my work? I don?t want parametric models like
2004 Oct 04
0
simulate bivariate life time distributions
Dear helpers, I was wondering if there are some bivariate distribution simulation functions in any R packages. Specifically, I want to simulate bivariate log logistic, bivariate Weibull, or other common bivariate life time functions, and I can specify the correlations. Any comments about this will be appreciated. Thanks, Zhu Wang
2006 Oct 06
0
Bivariate Weibull distribution -- Copula
"Jenny Stadt" <jennystadt at yahoo.ca> asked: > > I am struggling in a bivariate Weibull distribution although I > searched R-Site-Help and found suggestion with Copula. Seems the > maximum likelihood estimate is beyond what I can understand. > > My case is: given two known marginal distribution (both are Weibull), > and the correlation between them. How can I
2012 Dec 19
1
Theoretical confidence regions for any non-symmetric bivariate statistical distributions
Respected R Users, I looking for help with generating theoretical confidence regions for any of non-symmetric bivariate statistical distributions (bivariate Chi-squared distribution<Wishart distribution>, bivariate F-distribution, or any of the others). I want to to used it as a benchmark to compare a few strategies constructing confidence regions for non-symmetric bivariate data. There is
2013 Aug 26
0
Bivariate skew normal cdf; very slow
Dear all, I am calculating the bivariate skew normal cdf in "sn" package using "pmsn" function. Although it is quite convenient ( thanks to prof. Azzalini) but it seems to be slow. For example, it takes about 1 minute in calculation of 100k of such cdf values. I am thinking to write a c++ code for this although not very familiar with it. Any other idea?    Thanks in advance,
2008 Jan 23
2
from a normal bivariate distribution to the marginal one
Hello, I'm quite new with R and so I would like to know if there is a command to calculate an integral. In particular I simulated a bivariate normal distribution using these simple lines: rbivnorm <- function(n, # sample size mux, # expected value of x muy, # expected value of Y sigmax, # standard deviation of
2010 Jan 01
2
How to calculate density function of Bivariate binomial distribution
Am trying to do some study on bivariate binomial distribution. Anyone knows if there is package in R that I can use to calculate the density function of bivariate binomial distribution and to generate random samples of it. Thanks, -- View this message in context: http://n4.nabble.com/How-to-calculate-density-function-of-Bivariate-binomial-distribution-tp992002p992002.html Sent from the R help
2010 Dec 30
0
Bivariate weighted fit methods of Williamson-York in R?
Hello everyone, I've been looking for an R function to calculate bivariate weighted fits of my data set, preferably using methods of Williamson-York. Improvements offered by using bivariate weighted fitting compared to conventional linear least-square fitting was recently described in a paper by Cantrell (http://www.atmos-chem-phys.org/8/5477/2008/acp-8-5477-2008.pdf), in which the methods
2009 Feb 20
0
ML estimators of bivariate cauchy
Hi all, I am using the function COV.WT to estimate the estimators (location and scale) of a bivariate cauchy distribution. My doubt is about the option WT (weight), cause at the R-help shows that the weight is uniform according to the number of observations. But, checking the theory, for example, the mean is given by mean_estimator=mean(u(s)x)/mean(u(s)), where x=my data (bivariate)
2008 Jan 04
0
Bivariate normal equal-probability curve...
Good morning and I appreciate the availability of a help-list. I am a professional hydrologist, but not a professional statistician. Yet I find myself using statistical tools at least part of the time. My discovery of the R-project through a friend has been most helpful. Here is my problem: I'm tasked with fitting a dataset comprising correlated discharges from adjacent watersheds to
2006 Mar 29
2
bivariate case in Local Polynomials regression
Hi: I am using the package "KernSmooth" to do the local polynomial regression. However, it seems the function "locpoly" can only deal with univariate covaraite. I wonder is there any kernel smoothing package in R can deal with bivariate covariates? I also checked the package "lcofit" in which function "lcofit" can indeed deal with bivariate case. The
2012 Jul 27
3
bivariate normal
Dear list members I need a function that calculates the bivariate normal distribution for each observation. It is part of a likelihood function and I have 1000's of cases. As I understand it I cannot use packages like "mvtnorm" because it requres a covariance matrix of the same dimension as the number of observations. Basically what I need is a function that takes as arguments a