Displaying 11 results from an estimated 11 matches similar to: "Fw: Reversing data transformation"
2013 Apr 05
1
Reversing data transformation
Hi everybody,
I would be very grateful if you could give me your thoughts on the following issue.
I need to perform Box-Cox (bcPower) transformation on my data. To do this, I calculated lambda using the function 'powerTransform'.
powerTransform(data)
However, I got an error message when performing this function:
Convergence failure: return code = 52
I was told by John Fox
2013 Apr 06
1
Data normalization
Dear all,
I’m finding difficulties to normalize this data. Could you provide some input?
DATA:
c(0.000103113, 0.000102948, 0.000104001, 0.000103794, 0.000104628,
9.2765e-05, 9.4296e-05, 9.5025e-05, 9.4978e-05, 9.8821e-05, 9.7586e-05,
9.6285e-05, 0.00010158, 0.000100919, 0.000103535, 0.000103321,
0.000102842, 0.000102315, 0.0001033, 0.000103691, 0.000102689,
0.000103248, 0.000101216,
2013 Jan 31
1
Please, problem using “bcPower”
Hello,
I would like to perform a Box-Cox (“bcPower”) transformation on my data. For this, I am determining lambda using the “powerTransform” function. However, with one of my variables I get the following
Warning Message:
In estimateTransform(x, y, NULL, ...) :
Convergence failure: return code = 52 My variable is:
> x
[1] 0.0001031130 0.0001029480 0.0001040010 0.0001037940 0.0001046280
2023 Jul 08
1
Getting an error calling MASS::boxcox in a function
Dear Ron and Bert,
First (and without considering why one would want to do this, e.g.,
adding a start of 1 to the data), the following works for me:
------ snip ------
> library(MASS)
> BoxCoxLambda <- function(z){
+ b <- boxcox(z + 1 ~ 1,
+ lambda = seq(-5, 5, length.out = 101),
+ plotit = FALSE)
+ b$x[which.max(b$y)]
+ }
> mrow <- 500
2023 Jul 08
1
Getting an error calling MASS::boxcox in a function
Thanks John.
?boxcox says:
*************************
Arguments
object
a formula or fitted model object. Currently only lm and aov objects are handled.
*************************
I read that as saying that
boxcox(lm(z+1 ~ 1),...)
should run without error. But it didn't. And perhaps here's why:
BoxCoxLambda <- function(z){
b <- MASS:::boxcox.lm(lm(z+1 ~ 1), lambda = seq(-5, 5,
2023 Jul 08
1
Getting an error calling MASS::boxcox in a function
No, I'm afraid I'm wrong. Something went wrong with my R session and gave
me incorrect answers. After restarting, I continued to get the same error
as you did with my supposed "fix." So just ignore what I said and sorry for
the noise.
-- Bert
On Sat, Jul 8, 2023 at 8:28?AM Bert Gunter <bgunter.4567 at gmail.com> wrote:
> Try this for your function:
>
>
2023 Jul 08
1
Getting an error calling MASS::boxcox in a function
Hi Bert,
On 2023-07-08 3:42 p.m., Bert Gunter wrote:
> Caution: This email may have originated from outside the organization. Please exercise additional caution with any links and attachments.
>
>
> Thanks John.
>
> ?boxcox says:
>
> *************************
> Arguments
>
> object
>
> a formula or fitted model object. Currently only lm and aov objects
2013 Dec 12
1
boxcox transformations
Hi,
I am new to R.
I need help with regards to box cox transformation.
I have phenotypic data for e.g. plant height.
data is non-normal. Skewness is 0.34.
Could you please help me?
Regards,
Yogi
--
View this message in context: http://r.789695.n4.nabble.com/boxcox-transformations-tp4682077.html
Sent from the R help mailing list archive at Nabble.com.
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2013 Jan 17
0
powerTransform Warning Message
Hello,
I would like to perform a Box-Cox (“bcPower”) transformation on my data. For this, I am determining lambda using the “powerTransform” function. However, with one of my variables I get the following Warning Message:
In estimateTransform(x, y, NULL, ...) :
Convergence failure: return code = 52
My variable is:
> x
[1] 0.0001031130 0.0001029480 0.0001040010 0.0001037940 0.0001046280
2023 Nov 03
0
new cv package: cross-validation of regression models
Georges Monette and I would like to announce a new package, cv, now on
CRAN, which implements cross-validation of regression models.
Some of the functions supplied by the package:
- cv() is a generic function with a default method and computationally
efficient "lm" and "glm" methods, along with a method for a list of
competing models. There are also experimental
2023 Nov 03
0
new cv package: cross-validation of regression models
Georges Monette and I would like to announce a new package, cv, now on
CRAN, which implements cross-validation of regression models.
Some of the functions supplied by the package:
- cv() is a generic function with a default method and computationally
efficient "lm" and "glm" methods, along with a method for a list of
competing models. There are also experimental