Thank you for the advice. This is what I was looking for. If I would like
to label the axes, how can I do that? Specifically I would like to label
the x axis (AAA, AA, A, BBB) and same with the y axis.
jdr
On 7/17/06, Jim Lemon [EMAIL PROTECTED] wrote:
justin rapp wrote:
On the cover
On the cover of Zivot and Wang's Modeling Financial Time Series with S
Plus, there is a correlation plot that seems to indicate the strength
of correlation with color-coded squares, so that more highly
correlated stocks appear darker red. If anybody out there is familiar
with the book or
All,
I am using R on Mac OS X Tiger. I have assembled some graphs through quartz
and cut and pasted them into MSWord files on my Mac. I then emailed the
Word document containing the graphs to a Windows computer. Upon opening the
document, I received an error message telling me that the
All,
Happy World Cup and Wimbledon. This morning finds me with the first
of my many daily questions.
I am running a ks.test on residuals obtained from a regression model.
I use this code:
ks.test(Year5.lm$residuals,pnorm)
and obtain this output
One-sample Kolmogorov-Smirnov test
I have a vector containing players' weights. When I enter
mode(data.linear$Weight)
numeric is returned.
When I type mean(data.linear$Weight)
NA is returned.
Any ideas as to why this may be the case? I am trying to calculate
this ultimately so I can superimpose a normal density line over a
I have a dataset with a variable that is non-numeric. I was wondering
if there is an easy way in R to create a bar graph that will tell me
how many of each level of this non-numeric variable are in the overall
dataset.
Specifically, if my variable is LETTER, and I have A, B,C, D, E, F and
I want
This seems like a question that I should be able to answer on my own
but after looking at the documentation I cannot seem to find the
correct method.
How do I add lines to a bar plot that extend from the vertical axis?
For example, my vertical axis is numbered in increments of 10 and I
would like
I apologize for my constant questions but I am new to R and trying to
gain an appreciation for its capabilities. The following task is easy
in Excel and I was hoping somebody could give me a quick explanation
for how it can be acheived in R so I can avoid having to switch
between the two
made any adjustments to the code?
jdr
On 7/8/06, Duncan Murdoch [EMAIL PROTECTED] wrote:
On 7/8/2006 3:44 PM, justin rapp wrote:
I apologize for my constant questions but I am new to R and trying to
gain an appreciation for its capabilities. The following task is easy
in Excel and I
I am using the as.factor command to use with glm. When I use the command
maj - as.factor(data.logistic$Majors)
maj
I receive the following output:
[1] M M N M M M M N N M M M N M M M M M M M M M M M N M N N M M N M
M N M M M M M
[40] N M N M M N M M M N M N M N M N N N M N M M M M M M N M N
in
regressions be applied to linear regressions?
Thanks in advance for everyone's time and help.
jdr
--
Justin Rapp
409 S. 22nd St.
Apt. 1
Philadelphia, PA 19146
Cell:(267)252.0297
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predicted by the intercept and
independent variable x?
jdr
--
Justin Rapp
409 S. 22nd St.
Apt. 1
Philadelphia, PA 19146
Cell:(267)252.0297
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R-help@stat.math.ethz.ch mailing list
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PLEASE do read the posting guide
be greatly appreciated.
--
Justin Rapp
409 S. 22nd St.
Apt. 1
Philadelphia, PA 19146
Cell:(267)252.0297
[EMAIL PROTECTED]
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PLEASE do read the posting guide! http://www.R
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