Hi,
In my work, I often investigate relationships between highly skewed data.
Example:
set.seed(111)
require(MASS)
d = data.frame(mvrnorm(1000, mu=c(0,0), Sigma=matrix(c(1,.6,.6,1), nrow=2)))
names(d) = c("x","y")
## Skew Y
d$y = d$y^4
plot(d$x, d$y)
lines(lowess(d$x, d$y), lwd=2, col="blue")
Un
Perfect. Thanks!
On Tue, Mar 18, 2014 at 2:26 PM, Thomas Lumley wrote:
> On Tue, Mar 18, 2014 at 12:43 PM, Dustin Fife wrote:
>
>> I've got a dataset with really long column names (e.g.,
>> CYJ.OSU.OAV.UJC.BUT.RDI). What I'd like to do is replace the fourth peri
I've got a dataset with really long column names (e.g.,
CYJ.OSU.OAV.UJC.BUT.RDI). What I'd like to do is replace the fourth period
with a break ("\n") so that when it plots, it will not run off the page.
Here's what I've got so far:
create fake names function
fake.names = function(x){
pas
I have a list of variables of a variable length (e.g., Var1, Var2, Var3,
... Vark). What I want to do is somehow feed that information into the
paste function, like:
paste(Var1, Var2, Var3...)
The problem is that I don't want to hard-code it because it's wrapped
within a function. Is there a way
ot; "B1" "C1" "A2" "B2" "C2"
> A.K.
>
>
>
>
> On Tuesday, February 11, 2014 3:18 PM, Dustin Fife
> wrote:
> I have a list of variables of a variable length (e.g., Var1, Var2, Var3,
> ... Vark). What I want to do is somehow feed t
t; plotx(1:100,1:100,xlab="I Don't Work!")
> A.K.
>
>
> On Wednesday, February 5, 2014 11:14 AM, Dustin Fife <
> fife.dus...@gmail.com> wrote:
> Suppose I'm creating a function that sets default ylab and xlab behaviors:
>
> plotx = function(x, y, ...){
&
IBCO Software
> wdunlap tibco.com
>
>
>> -Original Message-
>> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
>> Behalf
>> Of Dustin Fife
>> Sent: Wednesday, February 05, 2014 8:11 AM
>> To: r-help
>
Suppose I'm creating a function that sets default ylab and xlab behaviors:
plotx = function(x, y, ...){
plot(x,y, ylab="", xlab="",...)
}
The problem is, on occasion, I actually want to override the defaults
in my function. I would like to do the following:
plotx(1:100, 1:100, xlab="I Don't
c1,vec1)[,3:1],1,paste,collapse=""))[1:n]
> }
> else {
> NA
> }
> res
> }
> fun1(0)
> #character(0)
> fun1(2)
> #[1] "A" "B"
>
> fun1(28)
> A.K.
>
>
>
>
> On Monday, January 27, 2014 4:41 PM, Dustin Fife
>
Hi all,
I frequently get requests to do data analysis where the person
references an excel column. e.g., "I want to analyze [insert complex
variable name], located at column AAQ in Excel." I've been doing is
gsub and inserting a part of the string for the complex variable name,
then going from th
;
> Hope this helps,
> Pascal
>
>
>
> 2013/9/5 Dustin Fife
>
>> I've been working on a way to visualize a spearman correlation. That
>> seemed
>> pretty simple:
>>
>> generate skewed data
>> x = rnorm(100)^2
>> y = .6*x + r
I've been working on a way to visualize a spearman correlation. That seemed
pretty simple:
generate skewed data
x = rnorm(100)^2
y = .6*x + rnorm(100, 0, sqrt(1-.6^2))
plot(x,y) regular plot
plot(rank(x),rank(y), xaxt="n", yaxt="n") ### spearman-like plot
make axis labels
axis(
Hi,
I'm doing research with biodata where I'm trying to predict disease state
from many biomarkers. Unfortunately it's not a common disease, so the
sample size is small. When I run the model as a glm, it has separation
issues.
Consequently, I ran the model using logistf with no problems. Now, how
'm using R 2.15.3 and I just installed the pan package today (version
.6)
--
Dustin Fife
PhD Student
Quantitative Psychology
University of Oklahoma
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.eth
mac? Is it up to
> date?
>
> (I would doubt that is.dag would be a recently written function.)
>
> ** **
>
> Bill Dunlap
>
> Spotfire, TIBCO Software
>
> wdunlap tibco.com****
>
> ** **
>
> *From:* Dustin Fife [mailto:fife.dus...@gmail.
>
>
> > -Original Message-
> > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf
> > Of Dustin Fife
> > Sent: Tuesday, January 29, 2013 8:52 AM
> > To: Duncan Murdoch
> > Cc: r-help
> > Subject: Re: [R] identify
ecause the
path goes from 1-2-3, then back into 1:
is.simple(graph(c(1,2,2,3,3,1,3,4)))
But, it returns TRUE.
On Tue, Jan 29, 2013 at 10:21 AM, Duncan Murdoch
wrote:
> On 29/01/2013 11:12 AM, Dustin Fife wrote:
>
>> Hi,
>>
>> I'm working on a project that will generate
tion is this: is there a better way to approach the problem? Is
there a more efficient way?
I know that I could probably identify which models are non-recursive after
estimation (via convergence failures or negative parameter estimates). But
I want to be able to identify them before estimation. Any help w
-
> > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> > On Behalf Of Steve Taylor
> > Sent: Sunday, January 20, 2013 3:22 PM
> > To: Dustin Fife; r-help
> > Subject: Re: [R] sem package, suppress warnings
> >
> > Have you t
still get warnings. I've also tried adding "check.analytic = FALSE,
debug = FALSE," and that doesn't seem to do it either. Any ideas why it's
not working?
It may be important to note that the command above is wrapped within a
function and I'm using "try()" to avoid
plot(x,y)
}
On Mon, Jul 9, 2012 at 6:03 PM, R. Michael Weylandt <
michael.weyla...@gmail.com> wrote:
> Take a look at ?layout
>
> Michael
>
> On Jul 9, 2012, at 5:15 PM, Dustin Fife wrote:
>
> > Let me start with an example:
> >
> > par(mfrow=c(2,3))
&g
ed? I think it looks weird to have them left-justified. Thanks in
advance for the help!
--
Dustin Fife
PhD Student
Quantitative Psychology
University of Oklahoma
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
n. I'm actually trying to do propensity score
matching to estimate the effect of treatment on a dichotomous variable.
Would the function change at all if the estimated effect is on a
dichotomous scale?
--
Dustin Fife
PhD Student
Quantitative Psychology
University of Oklahoma
[[alte
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
>
> -Oorspronkelijk bericht-----
> Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> Namens Dustin Fife
> Verzonden: dinsdag 29 mei 2012 14:56
> Aan: Ru
gt; # The same.
> linMod3 = lm(Y ~ 0 + I(X1 + X3) + X2, data=data.set)
> summary(linMod3)
>
> With set.seed(1) your common slope is
>
> coef(linMod2)
> I(X1 + X3) X2
> 0.4237869 3.3626984
>
> Also, I find it better to put 'library', 'require'
.
Unfortunately, the linearHypothesis is always compared to a full model
(where the parameters are freely estimated). I want to have an ANOVA
summary table for the reduced model. Any ideas? Thanks in advance for the
help!
--
Dustin Fife
PhD Student
Quantitative Psychology
University of Oklahoma
require me to learn a new syntax, and I guess
I'm just lazy. I'm comfortable with sem.
>
> On Thu, Dec 1, 2011 at 6:27 AM, Dustin Fife wrote:
> > Good idea. I'll give it a try. Thanks!
> >
> > On Thu, Dec 1, 2011 at 6:18 AM, John Fox wrote:
> >
&g
Good idea. I'll give it a try. Thanks!
On Thu, Dec 1, 2011 at 6:18 AM, John Fox wrote:
> Dear Dustin,
>
> > -Original Message-
> > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> > project.org] On Behalf Of Dustin Fife
> > Sent: Nove
, but I couldn't find anything in the documentation for the sem
package. Thanks!
--
Dustin Fife
Graduate Student
Quantitative Psychology
University of Oklahoma
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
]])
That seems to do just what I want. Thanks again John!
On Wed, Nov 9, 2011 at 5:40 PM, Dustin Fife wrote:
> Perfect! Thanks for the help.
>
> On Wed, Nov 9, 2011 at 4:27 PM, John Fox wrote:
>> Dear Dustin,
>>
>>> -Original Message-
>>> From: Dus
Perfect! Thanks for the help.
On Wed, Nov 9, 2011 at 4:27 PM, John Fox wrote:
> Dear Dustin,
>
>> -Original Message-----
>> From: Dustin Fife [mailto:fife.dus...@gmail.com]
>> Sent: November-09-11 2:12 PM
>> To: John Fox
>> Cc: r-help@r-project.org
>
r-
>> project.org] On Behalf Of Dustin Fife
>> Sent: November-09-11 10:57 AM
>> To: r-help@r-project.org
>> Subject: [R] path.diagram in SEM--display covariances without variances
>>
>> Forgive me if I'm posting to the wrong placeIt's my first
/plot', ignore.double=FALSE,
edge.labels="values", standardize=TRUE, min.rank=c("IWF", "SOF",
"PWF"))
The diagram is produces is hard to read because of the many variances
that are shown. The covariance estimates are important for my diagram,
but the var
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