search for: powertransform

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 0.0000927650 0.0000942960 [8] 0.0000950250...

...To: r-help@r-project.org ; R Help Subject: 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 that the nature of my data was probably causing the problem so I applied the following transformation: powerTransform(1e7*(data - 0.99*(mi...

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 0.0000927650 0.0000942960 [8] 0.00009502...

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 that the nature of my data was probably causing the problem so I applied the following transformation: powerTransform(1e7*(data - 0.99*(mi...

...> dd1 <- dd[, 1] # 1st column of dd > res <- boxcox(lm(dd1 + 1 ~ 1), lambda = seq(-5, 5, length.out = 101), plotit + = FALSE) > res$x[which.max(res$y)] [1] 0.2 > apply(dd, 2, BoxCoxLambda, simplify = TRUE) [1] 0.2 0.2 ------ snip ------ One could also use the powerTransform() function in the car package, which in this context transforms towards *multi*normality: ------ snip ------ > library(car) Loading required package: carData > powerTransform(dd + 1) Estimated transformation parameters Y1 Y2 0.1740200 0.2089925 I hope this helps, John...

...es <- boxcox(lm(dd1 + 1 ~ 1), lambda = seq(-5, 5, length.out = 101), > plotit > + = FALSE) > > res$x[which.max(res$y)] > [1] 0.2 > > > apply(dd, 2, BoxCoxLambda, simplify = TRUE) > [1] 0.2 0.2 > > ------ snip ------ > > One could also use the powerTransform() function in the car package, > which in this context transforms towards *multi*normality: > > ------ snip ------ > > > library(car) > Loading required package: carData > > > powerTransform(dd + 1) > Estimated transformation parameters > Y1 Y2 &...

...-5, 5, length.out = 101), >> plotit >> + = FALSE) >> > res$x[which.max(res$y)] >> [1] 0.2 >> >> > apply(dd, 2, BoxCoxLambda, simplify = TRUE) >> [1] 0.2 0.2 >> >> ------ snip ------ >> >> One could also use the powerTransform() function in the car package, >> which in this context transforms towards *multi*normality: >> >> ------ snip ------ >> >> > library(car) >> Loading required package: carData >> >> > powerTransform(dd + 1) >> Estimated transformation...

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: > >

...s. - selectStepAIC() is a model-selection procedure, suitable for use with cvSelect(), based on the stepAIC() function in the MASS package. - selectTrans() is a procedure for selecting predictor and response transformations in regression, also suitable for use with cvSelect(), based on the powerTransform() function in the car package. For additional information on using the cv package, see the "Cross-validation of regression models" vignette, in the package and at <https://cran.r-project.org/web/packages/cv/vignettes/cv.html>. The cv package is designed to be extensible to other...

...s. - selectStepAIC() is a model-selection procedure, suitable for use with cvSelect(), based on the stepAIC() function in the MASS package. - selectTrans() is a procedure for selecting predictor and response transformations in regression, also suitable for use with cvSelect(), based on the powerTransform() function in the car package. For additional information on using the cv package, see the "Cross-validation of regression models" vignette, in the package and at <https://cran.r-project.org/web/packages/cv/vignettes/cv.html>. The cv package is designed to be extensible to other...

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. [[alternative HTML version deleted]]