Would some type of multivariate SPC be useful? Potentially useful
options might include those based on SPC using PCA, or perhaps
Hotelling's T2.
Maybe you would find something useful in a package such as rrcov?
http://cran.r-project.org/web/packages/rrcov/vignettes/rrcov.pdf
R/S
Cliff
On Sun
n, Jan 3, 2011 at 12:03 AM, Clifford Long wrote:
> Dear R-help,
>
> I am attempting to plot data using standard R plot utilities. The
> data was retrieved from FRED (St. Louis Federal Reserve) using the
> package quantmod. My question is NOT about quantmod. While I
> retrieve d
Dear R-help,
I am attempting to plot data using standard R plot utilities. The
data was retrieved from FRED (St. Louis Federal Reserve) using the
package quantmod. My question is NOT about quantmod. While I
retrieve data using quantmod, I am not using its charting utility. I
have been having s
Hi Thomas,
Thanks for the additional information.
Just wondering, and hoping to learn ... would any lack of homogeneity of
variance (which is what I believe you mean by different stddev estimates) be
found when performing standard regression diagnostics, such as residual
plots, Levene's test (or
If you'll allow me to throw in two cents ...
Like Michael said, the dummy variable route is the way to go, but I believe
that the coefficients on the dummy variables test for equal intercepts. For
equality of slopes, do we need the interaction between the dummy variable
and the explanatory variab
implemented, which makes it difficult to
> judge which method is best (predict() or simulate(), and it is also unclear
> whether simulate() can be applied to glms (with family=gaussian or
> binomial).
>
> Any suggestions for how to proceed?
>
> Jacob
>
>
> On 12 Aug 2
Would the "predict" routine (using 'newdata') do what you need?
Cliff Long
Hollister Incorporated
On Wed, Aug 12, 2009 at 4:33 AM, Jacob Nabe-Nielsen wrote:
> Dear List,
>
> Does anyone know how to simulate data from a GLM object correponding
> to values of the independent (x) variable that do
message --
From: Clifford Long
Date: Sun, Jul 26, 2009 at 8:46 PM
Subject: Fwd: ROC curve using epicalc (after logistic regression)
To: cvira...@medicine.psu.ac.th
Dear Virasakdi Chongsuvivatwong,
After sending the message below to the R-help mailing list, it
occurred to me that I
Dear R-help list,
I'm attempting to use the ROC routine from the epicalc package after
performing a logistic regression analysis. My code is included after
the sessionInfo() result. The datafile (GasketMelt1.csv) is attached.
I updated both R and the epicalc packages and tried again before
send
Hi Myriam,
I'll take a stab at it, but can't offer elegance in the solution such
as the more experienced R folks might deliver.
I believe that the ARIMA function provides both point estimates and
their standard errors for the coefficients. You can use these as you
might a mean and standard error
22, 2009, at 6:16 PM, Clifford Long wrote:
>>
>>> Hi David,
>>>
>>> I appreciate the advice. I had coerced 'list4' to as.list, but forgot
>>> to specify "list=()" in the call to aggregate. I made the correction,
>>> and
ed index
= 0.003132 0.006264 0.009396 etc. What am I missing? Is there
a reference that I need to re-read? I would like to be able to plot
one against the other.
Thanks again for taking the time outside of your "day job" for your
earlier reply!
Cliff
On Mon, Jun 22, 2009 at 11:28
Hi R-list,
I'll apologize in advance for (1) the wordiness of my note (not sure
how to avoid it) and (2) any deficiencies on my part that lead to my
difficulties.
I have an application with several stages that is meant to simulate
and explore different scenarios with respect to product sales (in
Resending, as am not sure about the original "To:" address. Sorry for
any redundancy.
- Cliff
-- Forwarded message ------
From: Clifford Long
Date: Mon, Jun 22, 2009 at 11:04 AM
Subject: question about using _apply and/or aggregate functions
To: r-h...@lists.r-project.
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