[R] Re: errors in randomization test

CR Bleay, School Biological Sciences Colin.Bleay at bristol.ac.uk
Tue Jul 6 15:42:34 CEST 2004

dear rolf,

thank you for the assistance, i did not know how to catch the errors from 

of course the new code has thrown up a new error:
"Error in terms.default(object) : no terms component"

which i have to resolve.



--On Tuesday, July 6, 2004 9:23 am -0300 Rolf Turner <rolf at math.unb.ca> 

> Colin Bleay wrote:
>> last week i sent an e-mail about dealing with errors thrown up from a
>> glm.nb model carried out on multiple random datasets.
>> every so often a dataset is created which results in the following error
>> after a call to glm.nb:
>> "Error: NA/NaN/Inf in foreign function call (arg 1)
>> In addition: Warning message:
>> Step size truncated due to divergence"
>> I am at a loss as to how to deal with this.
>> firstly because the dataset that is generated, although throwing an
>> error  when the glm.nb model is applied, is a valid dataset. so how do i
>> incorporate this dataset in my results (results being descriptive stats
>> on  the coefficients from the multiple datasets) i.e. shoould
>> coefficients be  set to zero?
> 	Almost surely, setting the coefficients equal to 0 is the
> 	wrong thing to do.  What the right thing is depends on the
> 	answer to ``lastly''.
> 	Setting the coefficients to be NA in this case (i.e.
> 	effectively throwing away such cases) is also wrong, but not
> 	quite as wrong as setting them equal to 0.
>> secondly, how do i capture and deal with the error. is it possible to
>> construct an "if" statement so that "if error, do this, if not continue"
> 	This should be do-able using try().  Something like:
> 	c.list <- list()
> 	save.bummers <- list()
> 	K <- 0
> 	for(i in 1:42) {
> 		repeat {
> 			X <- generate.random.data.set()
> 			Y <- try(glm.nb(X,whatever))
> 			if(inherits(Y,"try-error")) {
> 				K <- K+1
> 				save.bummers[[K]] <- X
> 			} else break
> 		}
> 		c.list[[i]] <- coeff(Y)
> 	}
> 	This should give you a sample of 42 coefficient vectors from
> 	the ``successful'' data sets, and a list of all the (a random
> 	number of) data sets that yielded a lack of success.  You can
> 	then take the data sets stored in save.bummers and experiment
> 	with them to see what is causing the problem.
>> lastly, i am unsure as to what characteristics of a dataset would result
>> in  these errors in the glm.nb?
> 	Here I have to heed the advice (attributed to a ``great art
> 	historian'') from George F. Simmons' wonderful book on
> 	elementary differential equations:  ``A fool he who gives
> 	more than he has.''
> 					cheers,
> 						Rolf Turner
> 						rolf at math.unb.ca

Dr Colin Bleay
Dept. Biological Sciences,
University of Bristol,
Woodlands rd.,
BS8 1UG.

Tel: 44 (0)117 928 7470
Fax: 44 (0)117

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