Displaying 20 results from an estimated 10000 matches similar to: "recursive beta with cutoffs on large data set"
2009 Jan 16
2
Winsorizing Multiple Variables
Hi All,
I want to take a matrix (or data frame) and winsorize each variable.
So I can, for example, correlate the winsorized variables.
The code below will winsorize a single vector, but when applied to
several vectors, each ends up sorted independently in ascending order
so that a given observation is no longer on the same row for each
vector.
So I need to winsorize the variable but
2010 Aug 01
3
remove extreme values or winsorize – loop - dataframe
Hi everyone!
#I need a loop or a function that creates a X2 variable
that is X1 without the extreme values (or X1 winsorized)
by industry and year.
#My reproducible example:
firm<-sort(rep(1:1000,10),decreasing=F)
year<-rep(1998:2007,1000)
industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10),rep(6,10),rep(7,10),rep(8,10),rep(9,10),
rep(10,10)),1000)
X1<-rnorm(10000)
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,
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2008 Oct 22
3
Help finding the proper function
This might not be the correct forum for this question for there might be some
flaws in my logic so the R function I'm looking for might not be the
correct, but I know there?s a lot of smart people in this forum so please
correct me if I'm wrong. I have been googling and searching in this forum
for something useful but so far I'm out of luck.
This is the background to my problem. I
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
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
2020 Oct 09
2
2 D density plot interpretation and manipulating the data
> My understanding is that this represents bivariate normal
> approximation of the data which uses the kernel density function to
> test for inclusion within a level set. (please correct me)
You can fit a bivariate normal distribution by computing five parameters.
Two means, two standard deviations (or two variances) and one
correlation (or covariance) coefficient.
The bivariate normal
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
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 Feb 10
3
Sampling from Bivariate Uniform Distribution
Hello all!!!
1) I am wondering is there a way to generate random numbers in R for Bivariate Uniform distribution?
2) Does R have built-in function for generating random numbers for any given bivariate distribution.
Any help would be greatly appreciated !!
Good day!
Haneef Anver
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2011 Jun 14
2
How to generate bivariate exponential distribution?
Any one know is there any package or function to generate bivariate
exponential distribution? I gusee there should be three parameters, two rate
parameters and one correlation parameter. I just did not find any function
available on R. Any suggestion is appreciated.
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2004 Mar 17
3
Persp plotting of kernel density estimate.
Dear All,
I am trying to visualize the surface of a bivariate kernel density
estimate.
I have a vector of bivariate observations(x,y), and a function which
computes the kernel density estimate z corresponding to each
observation.
I cannot generate the (x,y) data in the ascending order needed by
persp(x,y,z).
I was wondering whether there is an R version of the S function interp.
Would anybody
2020 Oct 09
0
2 D density plot interpretation and manipulating the data
Hi Abby,
thank you for getting back to me and for this useful information.
I'm trying to detect the outliers in my distribution based of mean and
variance. Can I see that from the plot I provided? Would outliers be
outside of ellipses? If so how do I extract those from my data frame,
based on which parameter?
So I am trying to connect outliers based on what the plot is showing:
s <-
2009 Mar 07
4
multivariate integration and partial differentiation
Could somebody share some tips on implementing multivariate integration and partial differentiation in R?
For example, for a trivariate joint distribution (cumulative density function) of F(x,y,z), how to differentiate with respect to x and get the bivariate distribution (probability density function) of f(y,z). Or integrate f(x,y,z) with respect to x to get bivariate distribution of (y,z).
Your
2010 Apr 06
2
checking bivariate normality
x <- iris$Sepal.Length[1:50]/iris$Sepal.Width[1:50]
y <- iris$Petal.Length[1:50]/iris$Petal.Width[1:50]
I want to check whether (x,y) follows a bivariate normal distribution or
not, using density plot or scatter plot. Is it possible to plot a bivariate
density in R. I cant find any.
Arindam Fadikar
M.Stat
Indian Statistical Institute.
New Delhi, India
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2020 Oct 09
2
2 D density plot interpretation and manipulating the data
I recommend that you consult with a local statistical expert. Much of what
you say (outliers?!?) seems to make little sense, and your statistical
knowledge seems minimal. Perhaps more to the point, none of your questions
can be properly answered without subject matter context, which this list is
not designed to provide. That's why I believe you need local expertise.
Bert Gunter
"The
2004 Oct 23
4
Plotting Bivariate Normal Data
Dear list
I have a vector of values that allegedly have a bivariate normal distribution.
I want to create a plot that shows the values I have obtained, and the
bivariate normal distribution curve for the data.
Is there a way of doing this in R?
Many thanks for your help,
Sarah.
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2006 May 11
2
Maximum likelihood estimate of bivariate vonmises-weibull distribution
Hi,
I'm dealing with wind data and I'd like to model their distribution in
order to simulate data to fill-in missing values. Wind direction are
typically following a vonmises distribution and wind speeds follow a
weibull distribution. I'd like to build a joint distribution of
directions and speeds as a VonMises-Weibull bivariate distribution.
First is this a stupid question? I'm
2006 Apr 23
3
bivariate weighted kernel density estimator
Is there code for bivariate kernel density estimation?
For bivariate kernels there is
kde2d in MASS
kde2d.g in GRASS
KernSur in GenKern
(list probably incomplete)
but none of them seems to accept a weight parameter
(like density does since R 2.2.0)
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Erich Neuwirth, University of Vienna
Faculty of Computer Science
Computer Supported Didactics Working Group
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