This is the output I'm getting after the PFH code. What do the zeroes mean?
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Want to study the regime switching of a time series using MSGARCH package in Rstudio. After specifying the model, tried to fit the model using data of series using FitML function.I have used the following code to fit data.
msgarch_fit=FitML(msgarch_spec,data="log_ret") ## I have found the log return of the series and saved it in the vector named "log_ret".
But the following error is displayed.
"Error in f_check_y(data) : y must be numeric"
Being a beginner I can't understand the meaning of it. It would be of great help if someone can explain.
I tried to execute the code but error was displayed.
I was expecting to get the summary output.
Thank you
I'm using the latest version of the MDMR package in R to analyze whether there is a significant relationship between a set of independent and dependent variables. However, when I execute something like the following:
library(MDMR)
results<-mdmr(X=predictor_variable,D=distance_matrix)
I get 0.00199799899899874826986 as the output p-value.
However, when I try display it later with summary(results), it displays <0.002, and if I try to assign the value to a variable, 0 is assigned instead. I presume this is a floating point error in a calculation within R, but am clueless regarding how to fix it.
Running R 3.5.1 in R Studio.
I’ve edited pam.res$clustering to manually change the clusters.
Used silhouette() to try to observe the silhouette info for the edited clustering:
mahal<-D2.dist(data, cov.wt(data)$cov)
newsil<-silhouette(pam.res$clustering, mahal)
And all I get from summary(newsil) is
Mode NA’s
logical 1
I can’t reference within newsil, as it’s an atomic vector, which it shouldn’t be.
Can’t figure out what’s gone wrong. Any ideas? Thanks.
My question is with regards to creating a weighted box plot using ENmisc library. I have a dataframe and I want to plot the boxplot based on two different categories (both type chr).
The error given is ## Error: missing value where TRUE/FALSE needed from the line wtd.boxplot(df2J$mean_P32 ~ df2J$mode_Litho,weights=df2J$length). I've attached a log of the portion of code in question below which shows the values of each data type as well as that there is not any data missing. The last line produces a boxplot similar to the one I would expect from the line above.
Unfortunately I don't know how to recreate this error with a general example so I haven't provided code that can be run.
If anyone could shed some light on this error it would be much appreciated.
Other Info:
The plots work if I use the base package boxplot function.
There are other ways I could create weighted boxplots if needed such as this but I really don't see any reason this shouldn't work.
wtd.boxplot function
ENmisc library
I'm not sure why this doesn't show up in the Knitr ourput but The error that shows up in the R console is Error in if (any(out[nna])) stats[c(1, 5)] <- range(x[!out], na.rm = TRUE) :
missing value where TRUE/FALSE needed
I have the same problem and it happens because (I think) you have only 1 member for one of your groups. Check it.
I am trying to find a way to use distance weighted discrimination method (DWD) to remove biases from multiple microarray datasets.
My starting point is this. The problem is that Matlab version runs only under Windows, needs excel 5 format as input (where data appears to be truncated at line 65535 - matlab error is:
Error reading record for cells starting at column 65535. Try saving as Excel 98.
). Java version runs only with caBIG support, which, if I understood, has been shut down recently.
So I searched a lot and I find R/DWD package but from example I could not get how to provide the two datasets to merge to kdwd function.
Does anybody know how to use it?
Thanks
Try this, it has a DWD implementation
http://www.bioconductor.org/packages/release/bioc/html/inSilicoMerging.html