search for: corrplot

Hi Sarah, Thank you for your help. I tried using CR1<-as.matrix(CR1) but gives error Error in corrplot(CR1, method = "circle") : The matrix is not in [-1, 1]!. I am using a corrplot library. Please find the reproducible example: dput(head(CR1,10)) structure(c(26L, 46L, 39L, 38L, 47L, 59L, 56L, 61L, 43L, 60L, 78L, 63L, 2L, 58L, 8L, 1L, 1L, 9L, 11L, 2L, 1037500L, 46747L, 346300L, 672000L, 7...

Dear All, Please consider the following example library(corrplot) M <- cor(mtcars) corrplot(M, method="circle", type="lower", diag=F) Suppose that I want to have the label "mpg" at the top in black and leave everything else in red. How can I achieve that? Cheers Lorenzo

That does clarify for me that you're missing a step: I didn't clearly follow your description at first. corrplot expects a correlation matrix, not your original data. You need to use cor() first. That's pretty clear in the documentation. See for instance the examples: data(mtcars) M <- cor(mtcars) corrplot(M) Sarah On Sat, Mar 17, 2018 at 12:00 PM Shivi Bhatia <shivipmp82 at gmail.com> wrote:...

Created a new data set with 3 numeric variable to find correlation CR1<- mar%>% as_data_frame%>% select(AGE, OLD_CAR_PURCHASE_YRS, Total.Spend.With.AA) had to convert it to a data frame, code: as.matrix(as.data.frame(CR1)) Now i need to run a correlation plot for these 3 variables: corrplot(CR1, method = "circle") But i am getting this error: Error in matrix(unlist(value, recursive = FALSE, use.names = FALSE), nrow = nr, : length of 'dimnames' [2] not equal to array extent Researched and found Correlation <https://stackoverflow.com/questions/43362420/length-of-di...

I'm assuming you are using the corrplot package. If so, your data object does need to be a matrix, not a data frame. Since it's already a data frame, your line of code: as.matrix(as.data.frame(CR1)) doesn't need the as.data.frame function, but more importantly, you didn't assign the result to anything: as.matrix() does not...

Hi, I want to do a visualisation of a matrix plot made up of several plots of correlation matrices (using corrplot()). My data is in csv format. Here's an example: id,category,attribute1,attribute2,attribute3,attribute4 661,SCHS,43.2,0,56.5,1 12202,SCHS,161.7,5.7,155,16 1182,SCHS,21.4,0,29,0 1356,SSS, 8.8182,0.1818,10.6667,0.6667 1864,SCHS,443.7273,9.9091,537,46 12360,SOA,6.6364,0,10,0 3382,SOA,7.1667,0,26...

...ne discussion about a package on Bioconductor which should strengthen my proposal: http://grokbase.com/t/r/bioc-devel/129vxrxabm/to-use-knitr-how-to-write-the-right-makefile-for-bioconductor-devel-and-released-branch There are further advantages if package authors are not restricted to Sweave; the corrplot package is an example of building an HTML vignette which could be easier for authors who are not familiar with LaTeX and they can also distribute the vignette on the web easily. See: if (!require('corrplot')) install.packages('corrplot') help(package = 'corrplot', help_type...

...inly a bugfix-release. If you fit multi-response models, you are strongly engouraged to upgrade! The main changes since 1.2-0 are - Fixed bug in kernelpls.fit() that resulted in incorrect results when fitting mulitresponse models with fewer responses than predictors - Changed default radii in corrplot() - It is now possible to select the radii of the circles in corrplot See the file CHANGES in the sources for all changes. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: ort...

...inly a bugfix-release. If you fit multi-response models, you are strongly engouraged to upgrade! The main changes since 1.2-0 are - Fixed bug in kernelpls.fit() that resulted in incorrect results when fitting mulitresponse models with fewer responses than predictors - Changed default radii in corrplot() - It is now possible to select the radii of the circles in corrplot See the file CHANGES in the sources for all changes. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: ort...

Hello, I need help with a partial least square regression in R. I have read both the vignette and the post on R bloggers but it is hard to figure out how to do it. Here is the script I wrote: library(pls) plsrcue<- plsr(cue~fb+cn+n+ph+fung+bact+resp, data = cue, ncomp=7, na.action = NULL, method = "kernelpls", scale=FALSE, validation = "LOO", model = TRUE, x = FALSE, y =

Tengo una matriz de de datos (correlación) entre pares de muestras, de tipo diagonal inferior, de 250 y quisiera hacer un heatmap y/o un dendrograma. Soy un poco novato y me encuentro con el problema que no se como "importarla" para cargarla e indicar que se trata de una matriz de datos de tipo "diagonal inferior" para que R lo interprete y poder realizar un heatmap y/o

...edictions, validation statistics, coefficients, scores, loadings, biplots and correlation loadings. The main changes since 1.0-3 are - mvr, mvrCv and predict.mvr now has builtin support for scaling of X. - A new function stdize for explicit centering and/or scaling. - Correlation loadings plot (corrplot). - New argument `varnames' in coefplot, to label the x tick marks with the variable names. - loadingplot, coefplot and plot.mvrVal can now display legends, with the argument 'legendpos'. See CHANGES in the sources for all changes. -- Bj??rn-Helge Mevik and Ron Wehrens ________...

Hi all On page 39 of this paper [1] by Andrew Lo there is a very interesting correlation network diagram (sorry I dont have a more convenient link to the type of diagram I'm talking about). does anyone know of any package in R that can generate these types of diagrams? Cheers -- Rory [1] http://web.mit.edu/alo/www/Papers/august07.pdf [[alternative HTML version deleted]]

My apologies, to elaborate I carried out a correlation analysis and I want to plot the data (similar to the graphs available in the corrplot package. However, the results are as follows (I have many more combinations): AB 0.102 AC -0.002 BA -0.102 BC 0.270 CA 0.002 CB -0.270 I now want to create a matrix that uses the names from the first column as a "reference", so...

...edictions, validation statistics, coefficients, scores, loadings, biplots and correlation loadings. The main changes since 1.0-3 are - mvr, mvrCv and predict.mvr now has builtin support for scaling of X. - A new function stdize for explicit centering and/or scaling. - Correlation loadings plot (corrplot). - New argument `varnames' in coefplot, to label the x tick marks with the variable names. - loadingplot, coefplot and plot.mvrVal can now display legends, with the argument 'legendpos'. See CHANGES in the sources for all changes. -- Bj??rn-Helge Mevik and Ron Wehrens ________...

Hi all, I am having 4 vectors like Data: num [1:4, 1:32] -82.8 -81.8 -75.5 -107.6 -87.6 ...  and I want to calculate the correlation between those. Is there a graphical way in R to plot the correlations or not? I would like to thank you in advance for your help Regards Alex [[alternative HTML version deleted]]

Margarida Soares <margaridapmsoares at gmail.com> writes: > Thanks for your reply on pls! > I have tried to do a correlation plot but I get the following group of > graphs. Any way of having only 1 plot? > This is my script: > > corrplot(plsrcue1, comp = 1:4, radii = c(sqrt(1/2), 1), identify = FALSE, > type = "p" ) "Correlation loadings" are the correlations between each variable and the selected components, so I don't see how you can have more than two sets of correlations (i.e., more than two componen...

Dear R-users, I would like to process some spectroscopic data with R, and I was hoping some people might have some example code on how to do this. I would like to be able to do the following things: * Detect outlier-spectra -> This can be done by using scoreplot from the pls package * Determine the range of the spectrum to be used -> For this, I should be able to calculate the regression

...| bayesglm Bayesian generalized linear models. | bayespolr Bayesian Ordered Logistic or Probit Regression | binnedplot Binned Residual Plot | coefplot Generic Function for Making Coefficient Plot | contr.bayes.ordered Contrast Matrices | corrplot Correlation Plot | display Functions for Processing lm, glm, mer and polr | Output | fround Formating the Rounding of Numbers | invlogit Inverse logistic function | lalonde Lalonde Dataset | match...

Hi I have dataset that consists of two columns AB 0.102 AC -0.002 BA -0.102 BC 0.270 CA 0.002 CB -0.270 I wish to create a matrix so that I can eventually plot the data. A B C A 1 0.102 -0.002 B -0.102 1 0.27 C 0.002 -0.27 1 Any help or guidance would be greatly