he slaves operate in this way, but it's
only been a minor inconvenience for me in any event.
Chris
On 9 February 2011 03:36, Patrick Connolly wrote:
> On Tue, 01-Feb-2011 at 11:01AM -0500, Chris Carleton wrote:
>
> [...]
>
> |>
> |> My output is as follows;
> |>
&
Hi All,
I'm trying to parallelize some code using Rmpi and I've started with a
sample 'hello world' program that's available at
http://math.acadiau.ca/ACMMaC/Rmpi/sample.html. The code is as
follows;
# Load the R MPI package if it is not already loaded.
if (!is.loaded("mpi_initialize")) {
Hi List,
I'm using npRmpi to run some density equality tests and place the
output into a matrix. I've put together some crude functions for the
purpose, but I'm receiving the following error when npdeneqtest()
reached the bootstrap;
FATAL ERROR: Memory allocation failure (type DBL_VECTOR). Progra
Thanks for the suggestion. The solution below is much better than my
round-about way.
combn(outcomes, 2, list )
I can't do much about the speed of combn() so I wanted to trim the fat
wherever else I could.
C
On 17 November 2010 15:10, Charles C. Berry wrote:
>
> On Wed, 17 Nov
Hi List,
I'm hoping to get opinions for enhancing the efficiency of the following
code designed to take a vector of probabilities (outcomes) and calculate a
union of the probability space. As part of the union calculation, combn()
must be used, which returns a matrix, and the parallelized version
ject. 'pdf_pred' is a dataframe that holds
the values and allows me to search for the result ('prob') on the basis of
the 'cat' column thus maintaining my database integrity. It's perfectly
acceptable for you to choose not to offer support on a volunteer help
mai
re were too many 1s floating around for me to figure out if you
> wanted to find elements of a that matched the entire vector or
> subelements of a that matched elements of the vector (if that makes
> any sense).
>
> HTH,
>
> Josh
>
> On Mon, Nov 15, 2010 at 1:24 PM, Ch
Sorry folks, I keep forgetting to switch to my r-help email to send the
replies so they get unintentionally sent to a moderator (particularly sorry
for that moderators...)
C
-- Forwarded message --
From: Chris Carleton
Date: 15 November 2010 17:07
Subject: Re: [R] indexing lists
Hi List,
I'm trying to work out how to use which(), or another function, to find the
top-level index of a list item based on a condition. An example will clarify
my question.
a <- list(c(1,2),c(3,4))
a
[[1]]
[1] 1 2
[[2]]
[1] 3 4
I want to find the top level index of c(1,2), which should return
Hi Peter and List,
I realized the err of my ways here. Thanks for the response; I appreciate
the help. The struggles of self-taught statistics and maths continue!
Chris
On 15 November 2010 04:34, P Ehlers wrote:
> Chris Carleton wrote:
>
>> Hi List,
>>
>> I'm try
Hi again List,
By 'discrete' variable in the last email, I meant 'categorical'. Also, the
data I sent is one of the samples of the main data frame, which I mentioned
in a round-about way, but I thought that it might be confusing after reading
the email again. Thanks again for any help,
Chris
Hi List,
I'm trying to get a density estimate for a point of interest from an npudens
object created for a sample of points. I'm working with 4 variables in total
(3 continuous and 1 unordered discrete - the discrete variable is the
character column in training.csv). When I try to evaluate the den
Hello List,
I'm trying to find a convenient way of performing a weighted convolution on
multiple n-dimensional kernel density estimates (n-d pdfs) produced by the
np package function npudens()/npudist(). Are there any functions in R that
will take a list of functions and a list of weights and conv
ciated,
Chris
> CC: r-help@r-project.org
> From: dwinsem...@comcast.net
> To: w_chris_carle...@hotmail.com
> Subject: Re: [R] Time Series Data
> Date: Fri, 27 Nov 2009 10:10:36 -0500
>
>
> On Nov 27, 2009, at 9:55 AM, chris carleton wrote:
>
> >
> > Hi Al
Hi All,
I'm trying to analyze some time series data and I have run into difficulty. I
have decadal sun spot data and I want to separate the very regular periodic
function from the trend and noise. I looked into using stl(), but the frequency
of the time series data must be greater than 1 for s
Hi All,
I was hoping someone could save me the trouble of reading through source code
and answer a quick question of mine regarding poly(). Does the poly() function
use a classical orthogonal polynomial series to fit polynomial models, or does
poly() generate a unique series of orthogonal poly
Hi Everyone,
I'm continuing to run into trouble with polyfit. I'm using the fitting function
of the form;
fit <- lm(y ~ poly(x,degree,raw=TRUE))
and I have found that in some cases a polynomial of certain degree can't be
fit, the coefficient won't be calculated, because of a singularity. If I
ject.org
> From: r.tur...@auckland.ac.nz
> Subject: Re: [R] Polynomial Fitting
> Date: Wed, 30 Sep 2009 08:30:15 +1300
> To: w_chris_carle...@hotmail.com
>
>
> On 30/09/2009, at 5:34 AM, chris carleton wrote:
>
> >
> > Thanks for the response. I'm sorry I didn
sponding x values from the data before
fitting the poly and the result was the same coefficients. Thanks very much to
anyone who is willing to provide information.
Chris Carleton
> CC: r-help@r-project.org
> From: r.tur...@auckland.ac.nz
> Subject: Re: [R] Polynomial Fitting
> Date: T
function would be different in R? Thanks,
Chris Carleton
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