When I try to calculate Gest in spatstat I get the error:
bootstrap output matrix missing.
Does anyone know what am I doing wrong?
I think that "bootstrap output matrix missing" is a fairly generic error, and (unless someone has explicit experience with your case) I would imagine that more information is needed to solve this.
Without more information, I would suggest that you debug the Gest function. You have two good options for that:
1) Use the debug() function:
debug(Gest)
Now run your code. Then you can walk through the Gest function and see where is breaks. Before that point, look at all the environment variables by (for instance) using ls() and see if any assumptions are broken. Presumably something isn't being set correctly.
2) Use recover:
option(error=recover)
Then you will go into browser mode whenever the error occurs, and you can explore the workspace at that point.
This error message does not originate from the spatstat package.
To identify the location of the error, type traceback() immediately after the error has occurred. This will give you a list of the nested commands that were being executed at the time the error occurred. The top one is the location which raised the error.
Related
I am running a very long simulation, and about 1 in every 20 iterations a model fails to converge which trashes the whole thing.
I know I can use try() with the offending model to skip past it in the event of an error, but I was wondering if this could be extended into a conditional? By which I mean if an error did occur, it would execute another short script instead of the code that caused the error. Kind of like an if statement for errors.
Thank you all.
You can use tryCatch function, a tutorial can be found here:
https://www.r-bloggers.com/2012/10/error-handling-in-r/
I have written a small program in R, and when I get to this following line:
i=which(grepl(yyyy.q, Metrop$year))+1
I get the following error message:
Error in grepl(yyyy.q, Metrop$year) : object 'yyyy.q' not found
I think maybe this is occurring because I haven't defined 2019.3 as the current "yyyy.q". And that is what I need to do in order to tell R to start forecasting according to my model. Does that seem like the likely problem? I thought that was the problem but have struggled to fix it.
Here is how I am defining things in the beginning of my program before I get to the actual model specification, I assume the full code isn't necessary, but happy to share if that helps.
Metrop<-Houston
name<-"National"
Metrop<-Metrop[Metrop$year>=1989.4,]
Screenshot of dataset
Thanks for you help. Happy to share any more code or data if necessary.
I was running a spatstat envelop to generate simulations sample, however, it got stuck and did not run. So, I attempted to close the application but fail.
RStudio diagnostic log
Additional error message:
This application has requested the Runtime to terminate it in an
unusual way. Please contact the application's support team for more
information
There are several typing errors in the command shown in the question. The argument rank should be nrank and the argument glocal should be global. I will assume that these were typed correctly when you ran the command.
Since global=TRUE this command will generate 2 * nsim = 198 realisations of a completely random pattern and calculate the L function for each one of them. In my experience it should take only a minute or two to compute this, unless the geometry of the window is very complicated. One hour is really extraordinary.
So I'm guessing either you have a very complicated window (so that the edge correction calculation is taking a long time) or that RStudio is hanging somehow.
Try setting correction="border" or correction="none" and see if that makes it run faster. (These are the fastest choices.) If that works, then read the help for Lest or Kest about edge corrections, and choose an edge correction that you like. If not, then try running the same command in R instead of RStudio.
I'm using keras package in R, and would like to define a custom loss function.
While I was able to find a few examples (one of them), there was nothing on how to debug your own loss function. That is, even if I make it work, how could I verify that it works correctly (e.g. take some y_true and y_pred, and go through the calculations)?
I tried adding a print statement inside the function, but nothing came out.
As title, I have collected data for 1:6 matched case-control study and I am trying to analyze the data using matchTab, but it gives me error "subscript out of bounds", I wonder if anyone here has met anything similar before. What does it mean? Some issue about my dataset? As I have tried the manual, I can get the result using the dataset used in the manual.
Thanks.
That error often arises from matrix subsetting beyond the dimensions of the object. Try this for example:
mat <- matrix(1:9, ncol = 3)
mat[,4]
with the last line yielding
> mat[,4]
Error: subscript out of bounds
This sometimes happens in code because the programmer forgot that [ drops empty dimensions - I've done this myself many times, forgetting the 1 column matrix case! I'm not saying this is the problem here, but is one common cause of it in R code.
As you haven't provided a reproducible example and I am unfamiliar with the package you mention, I can't diagnose the problem further. It could be a bug in their package or a problem with how you have supplied, or understood you needed to supply, data to the function.
First thing I would do is re-read the man page for the function. Confirm you have the arguments supplied correctly. If that doesn't help, rerun to generate the error and then call traceback() to see exactly in what function the error is being raised. To debug further, try
options(error = recover)
then rerun your code. This will drop you into the debugger so you can go into the frame where the error occurred and see what all the objects were like, how they were sized etc. and why the error was being raised.
If you are not up to debugging this yourself, you might need to contact the maintainers, or provide a reproducible example...