Thanks John.
I have one observation data point with a value that's exactly equal to the
predicted value, therefore the residual is 0. Would this be the reason
you mentioned below?
From: "John Fox"
To: Liang Che/US/TLS/PwC@Americas-US
Cc: "'Sanford We
Can someone please help with the below - thanks!
Warning messages:
1: Not plotting observations with leverage one:
7
2: Not plotting observations with leverage one:
7
> print(qqPlot(fit),envelop=.95);
Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels =
TRUE) :
variable lengt
Can someone please help with the error message below -- thanks!
Warning messages:
1: Not plotting observations with leverage one:
7
2: Not plotting observations with leverage one:
7
> print(qqPlot(fit),envelop=.95);
Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels =
TRUE) :
Can someone please help with the error message below?
Warning messages:
1: Not plotting observations with leverage one:
7
2: Not plotting observations with leverage one:
7
> print(qqPlot(fit),envelop=.95);
Error in model.frame.default(formula = Y ~ X - 1, drop.unused.levels =
TRUE) :
variable
For example:
How to make R write out:
Balance = 2 + 3 * IntGDP + 5 * IntUnemployment + 0.3 * d1
from the table below:
Balance Intercept IntGDP GDPNum IntUnemployment
IntInflationd1 d2 d3
3 2 3 5 0.3 0 0
will add() or drop() function work more similarly as SAS?
I understand that there are not many observation points which might cause
the problem, but why can the automated process run successfully in SAS
instead?
From: David Winsemius
To: Liang Che/US/TLS/PwC@Americas-US
Cc:
Date
one extra question
How do I export the final image (with plots and lines added) into files in
a batch mode for a bunch of regressions?
thanks
- Forwarded by Liang Che/US/TLS/PwC on 10/08/2012 08:48 PM -
From: Liang Che/US/TLS/PwC
To: Joseph Clark @INTL
Cc: r-help@r
thank you all for your answers
i have figured out the plot i wanted - it was actually pretty easy
lines(x=20:34,prd[,1],col="red",Ity=1)
lines(x=20:34,prd[,2],lty=2)
lines(x=20:34,prd[,3],lty=2)
From: Joseph Clark
To: Liang Che/US/TLS/PwC@Americas-US
Cc:
Date: 10/
Ran a bunch of variables in R and the final result of StepAIC is as below:
Why are the first 5 variables kept in the stepwise result?? Are the last
4 variables finally chosen after Stepwise? Thanks
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.315e-01 2.687e-01 0.490 0.6361
- x :
the condition has length > 1 and only the first element will be used
From: Joseph Clark
To: Liang Che/US/TLS/PwC@Americas-US
Cc:
Date: 10/08/2012 05:06 PM
Subject:RE: [R] How to use Lines function to draw the error bars?
In my example code, 'fit'
From: Joseph Clark
To: Liang Che/US/TLS/PwC@Americas-US,
Date: 10/08/2012 04:03 PM
Subject:RE: [R] How to use Lines function to draw the error bars?
I typically use the function "plotCI" from the "plotrix" package for
confidence intervals or error bars
Thanks -- I got this message:
Error in stripchart.default(x1, ...) : invalid plotting method
From: Bita Shams
To: Liang Che/US/TLS/PwC@Americas-US
Date: 10/08/2012 03:41 PM
Subject:Re: [R] How to use Lines function to draw the error bars?
try this :
plot(new,prd[,3
For a set of data showing seasonality (related to the 4th quarter), ncv
test in R shows p-value of 0.008 which rejects the null hypothesis of
constant-variance. How to apply White's standard error in R?
thanks
__
The i
fit lwrupr
1 218.4332 90.51019 346.3561
2 218.3906 90.46133 346.3198
3 218.3906 90.46133 346.3198
4 161.3982 44.85702 277.9394
5 192.4450 68.39903 316.4909
6 179.8056 56.49540 303.1158
7 219.5406 91.52707 347.5542
8 162.6761 46.65760 278.6945
9 193.8506 70.59
For a set of data showing seasonality (related to the 4th quarter),
ncv
test shows p-value of 0.008 which rejects the null hypothesis of
constant-variance. Currently a linear LM relationship is being
applied to
the data.
Should white's error be used to correct the non-cons
For example, if coefficient's p-value is less than 0.1 I want the stepwise
to automatically drop that variable. Can the stepAIC be customized to do
that? SAS seems to be able to customized stepwise function with p-value
or cooks'd.
thanks!
Can someone please help with the error message below?
thanks!
Start: AIC=-Inf
value ~ 1 + Core_CPI__ + GDP_change + Unemployment + housing +
interest + S_P + d1 + d2 + d3
Error in if (any(ch)) { : missing value where TRUE/FALSE needed
In addition: Warning message:
attempting model select
See error message below: can someone please help with this? Thanks!
Residuals:
ALL 9 residuals are 0: no residual degrees of freedom!
Residual standard error: NaN on 0 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: NaN
F-statistic: NaN on 8 and 0 DF, p-value: NA
My stepAIC function works for one set of data but not anotherone set
of data shows the steps of eliminating variables, versus another set of
data doesn't throw away any variables.
Can anyone please explain why? Thanks
__
T
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