distance results codes

Statistics are stored in the Distance project using a series of numeric codes. This is a quick guide to interpreting these codes.

Codes are 4 digits

1. a "module" code
2. ??? (always zero?)
3. a "statistic" code
4. "type" of statistic

Look-up for 1. and 3. is in the tables below.

Tables of codes

From the Distance manual

Taken from the Distance for Windows user manual (p 322-323):

Module code	Module	Statistic code	statistic
1	encounter rate	1	number of observations (n)
	2	number of samples (k)
	3	effort (L or K or T)
	4	encounter rate (n/L or n/K or n/T)
	5	left truncation distance
	6	right truncation distance (w)
2	detection probability	1	total number of parameters (m)
	2	AIC value
	3	chi-square test probability
	4	f(0) or h(0)^1
	5	probability of detection (Pw)^1
	6	effective strip width/detection radius (ESW/EDR)^1
	7	AICc
	8	BIC
	9	Log likelihood
	10	Kolmogorov-Smirnov test probability
	11	Cramér-von Mises (uniform weighting) test probability
	12	Cramér-von Mises (cosine weighting) test probability
	13	key function type^2
	14	adjustment series type^3
	15	number of key function parameters (NKP)
	16	number of adjustment term parameters (NAP)
	17	number of covariate parameters (NCP)
	101 ... (100+m)	estimated value of each parameter^5
3	cluster size	1	average cluster size^1
	2	size-bias regression correlation ( r)
	3	p-value for correlation significance (r-p)
	4	estimate of expected cluster size corrected for size bias^1
4	density/abudance	1	density of clusters (or animal density if non-clustered)^1
	2	density of animals^1
	3	number of animals, if survey area is specified^1
	4	bootstrap density of clusters^14
	5	bootstrap density of animals^14
	6	bootstrap number of animals^14

Footnotes:

1. Values for CV, LCL, UCL and DF are included for these statistics.
2. Key function types are:
   1. uniform
   2. half-normal
   3. negative exponential
   4. hazard rate
3. Adjustment series types are:
   1. simple polynomial
   2. Hermite polynomial
   3. cosine
4. Bootstrap CV calculated as bootstrap SE / bootstrap point estimate; df field here is the number of bootstraps
5. Statistic 101 corresponds with the parameter identified as A(1) in the results, 102 with A(2), etc.

From DistIni.mdb

The table "ProjectSettings" provides the following information:

Key	Setting

1  | Number of sampler points

100 | Mean coverage probability 1000 | AIC - (minimum AIC), calculated within survey and data filter 1001 | AICc - (minimum AICc), calculated within survey and data filter 1002 | BIC - (minimum BIC), calculated within survey and data filter 1003 | LogL - (minimum LogL), calculated within survey and data filter 101 | Minimum coverage probability 1010 | Number of observations 102 | Maximum coverage probability 1020 | Number of samples 103 | Standard deviation of coverage probability 1030 | Total survey effort 1040 | Encounter rate 1041 | Encounter rate coeff. of var. 1042 | Encounter rate lower conf. limit 1043 | Encounter rate upper conf. limit 1044 | Encounter rate degrees of freedom 2 | Number of sampler points 2010 | Total number of parameters 2020 | Akaike Information Criterion (AIC) value 2030 | Goodness-of-fit chi-square test probability (test 1, after pooling) 2040 | Probability density function (line transects) or slope of the pdf (point transects) at x=0 2050 | Probability of detection 2051 | Probability of detection coeff. of var. 2052 | Probability of detection lower conf. limit 2053 | Probability of detection upper conf. limit 2054 | Probability of detection degrees of freedom 2060 | Effective strip width/detection radius 2061 | Effective strip width/detection radius coeff. of var. 2062 | Effective strip width/detection radius lower conf. limit 2063 | Effective strip width/detection radius upper conf. limit 2064 | Effective strip width/detection radius degrees of freedom 2070 | Small-sample adjusted Akaike Information Criterion value 2080 | Bayes' Information Criterion 2090 | Log likelihood 2100 | Goodness-of-fit Kolmogorov Smirnov test probability 2110 | Goodness-of-fit Cramer-von Mises (uniform weighting) test probability 2120 | Goodness-of-fit Cramer-von Mises (cosine weighting) test probability 2150 | Number of key function parameters 2160 | Number of adjustment term parameters 2170 | Number of covariate parameters 3 | Number of sampler lines 3010 | Mean cluster size 3011 | Mean cluster size coeff. of var. 3012 | Mean cluster size lower conf. interval 3013 | Mean cluster size upper conf. interval 3014 | Mean cluster size degrees of freedom 3020 | Size bias regression correlation coefficient 3030 | Size bias regression correlation test probability 3040 | Expected cluster size, correcting for size bias 3041 | Expected cluster size coeff. of var. 3042 | Expected cluster size lower conf. limit 3043 | Expected cluster size upper conf. limit 3044 | Expected cluster size degrees of freedom 4 | Maximum possible area coverage 4010 | Density of clusters 4011 | Density of clusters analytic coeff. of var. 4012 | Density of clusters analytic lower conf. limit 4013 | Density of clusters analytic upper conf. limit 4014 | Density of clusters degrees of freedom 4020 | Density of individuals 4021 | Density of individuals analytic coeff. of var. 4022 | Density of individuals analytic lower conf. limit 4023 | Density of individuals analytic upper conf. limit 4024 | Density of individuals degrees of freedom 4030 | Number of individuals 4031 | Number of individuals analytic coeff. of var. 4032 | Number of individuals analytic lower conf. limit 4033 | Number of individuals analytic upper conf. limit 4034 | Number of individuals analytic degrees of freedom 4040 | Density of clusters bootstrap 4041 | Density of clusters bootstrap coeff. of var. 4042 | Density of clusters bootstrap lower conf. limit 4043 | Density of clusters bootstrap upper conf. limit 4050 | Density of individuals bootstrap 4051 | Density of individuals bootstrap coeff. of var. 4052 | Density of individuals bootstrap lower conf. limit 4053 | Density of individuals bootstrap upper conf. limit 4060 | Number of individuals bootstrap 4061 | Number of individuals bootstrap coeff. of var. 4062 | Number of individuals bootstrap lower conf. limit 4063 | Number of individuals upper confidence limit 4064 | Number of bootstrap resamples 5 | Realized area coverage 5010 | Generalized cross-validation metric for DSM model 5020 | Sample size (number of segments) for DSM model 5030 | Proportion of deviance explained by DSM model 5040 | The estimated scale parameter/error variance 6 | Proportion of survey area covered 7 | Mean realized sampler line length (mean over strata)