Input.interp

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input.interp is an R function that interprets model inputs from a user-friendly format into explicit and exact mathematical format. The purpose is to make it easy for a user to give input without a need to worry about technical modelling details.

Question

What should be a list of important user input formats, and how should they be interpreted?

Answer

The basic feature is that if a text string can be converted to a meaningful numeric object, it will be. This function can be used when data is downloaded from Opasnet Base: if Result.Text contains this kind of numeric information, it is converted to numbers and fused with Result.

n is the number of iterations in the model. # is any numeric character in the text string.

Example	Regular expression	Interpretation	Output in R
12 000	# #	12000. Text is interpreted as number if space removal makes it a number.	as.numeric(gsub(" ", "", Result.text))
12,345	#,#	12.345. Commas are interpreted as decimal points.	as.numeric(gsub(",", ".", Result.text)) # Note! Do not use comma as a thousand separator!
-14,23	-#	-14.23. Minus in the beginning of entry is interpreted as minus, not a sign for a range.
50 - 125	# - #	Uniform distribution between 50 and 125	data.frame(obs=1:n, result=runif(n,50,125))
-12 345 - -23,56		Uniform distribution between -12345 and -23.56.
1 - 50	# - #	Loguniform distribution between 1 and 50 (Lognormality is assumed if the ratio of upper to lower is => 30)
or 3.1 +- 1.2|# ± # or # +- #	Normal distribution with mean 3.1 and SD 1.2	data.frame(obs=1:n, result=rnorm(n,3.1,1.2))
2.4 (1.8 - 3.0)	# (# - #)	Normal distribution with mean 2.4 and 95 % confidence interval from 1.8 to 3.0	data.frame(obs=1:n, result=rnorm(n,2.4,(3.0-1.8)/2/1.96))
2.4 (2.0 - 3.2)	# (# - #)	Lognormal distribution with mean 2.4 and 95 % confidence interval from 2.0 to 3.0. Lognormality is assumed if the difference from mean to upper limit is => 50 % greater than from mean to lower limit.
24 - 35 (odds 5:1)	# - # (odds #:#)	Interpretation: odds is five to one that the truth is between 24 and 35. How to calculate this, I don't know yet, but there must be a prior.