Convenience function for calculating (traditional) PSD-X and (incremental) PSD X-Y values for all Gabelhouse lengths and increments thereof.
psdCalc(formula, data, species, units = c("mm", "cm", "in"), method = c("multinomial", "binomial"), conf.level = 0.95, addLens = NULL, addNames = NULL, justAdds = FALSE, what = c("all", "traditional", "incremental", "none"), drop0Est = TRUE, showIntermediate = FALSE, digits = 0)
formula | A formula of the form |
---|---|
data | A data.frame that minimally contains the observed lengths given in the variable in |
species | A string that contains the species name for which Gabelhouse lengths exist. See |
units | A string that indicates the type of units used for the lengths. Choices are |
method | A character that identifies the confidence interval method to use. See details in |
conf.level | A number that indicates the level of confidence to use for constructing confidence intervals (default is |
addLens | A numeric vector that contains minimum lengths for additional categories. See |
addNames | A string vector that contains names for the additional lengths added with |
justAdds | A logical that indicates whether just the values related to the length sin |
what | A string that indicates the type of PSD values that will be printed. See details. |
drop0Est | A logical that indicates whether the PSD values that are zero should be dropped from the output. |
showIntermediate | A logical that indicates whether the number of fish in the category and the number of stock fish (i.e., “intermediate” values) should be included in the returned matrix. Default is to not include these values. |
digits | A numeric that indicates the number of decimals to round the result to. Default is zero digits following the recommendation of Neumann and Allen (2007). |
A matrix with columns that contain the computed PSD-X or PSD X-Y values and associated confidence intervals. If showIntermediate=TRUE
then the number of fish in the category and the number of stock fish will also be shown.
Computes the (traditional) PSD-X and (incremental) PSD X-Y values, with associated confidence intervals, for each Gabelhouse length. All PSD-X and PSD X-Y values are printed if what="all"
(DEFAULT), only PSD-X values are printed if what="traditional"
, only PSD X-Y values are printed if what="incremental"
, and nothing is printed (but the matrix is still returned) if what="none"
.
Confidence intervals can be computed with either the multinomial (Default) or binomial distribution as set in method
. See details in psdCI
for more information.
Point estimate calculations match those constructed "by hand."
6-Size Structure.
Ogle, D.H. 2016. Introductory Fisheries Analyses with R. Chapman & Hall/CRC, Boca Raton, FL.
Guy, C.S., R.M. Neumann, and D.W. Willis. 2006. New terminology for proportional stock density (PSD) and relative stock density (RSD): proportional size structure (PSS). Fisheries 31:86-87. [Was (is?) from http://pubstorage.sdstate.edu/wfs/415-F.pdf.]
Guy, C.S., R.M. Neumann, D.W. Willis, and R.O. Anderson. 2006. Proportional size distribution (PSD): A further refinement of population size structure index terminology. Fisheries 32:348. [Was (is?) from http://pubstorage.sdstate.edu/wfs/450-F.pdf.]
Neumann, R. M. and Allen, M. S. 2007. Size structure. In Guy, C. S. and Brown, M. L., editors, Analysis and Interpretation of Freshwater Fisheries Data, Chapter 9, pages 375-421. American Fisheries Society, Bethesda, MD.
Willis, D.W., B.R. Murphy, and C.S. Guy. 1993. Stock density indices: development, use, and limitations. Reviews in Fisheries Science 1:203-222. [Was (is?) from http://web1.cnre.vt.edu/murphybr/web/Readings/Willis%20et%20al.pdf.]
## Random length data # suppose this is yellow perch to the nearest mm yepdf <- data.frame(yepmm=round(c(rnorm(100,mean=125,sd=15),rnorm(50,mean=200,sd=25), rnorm(20,mean=300,sd=40)),0), species=rep("Yellow Perch",170)) psdCalc(~yepmm,data=yepdf,species="Yellow perch",digits=1)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-Q 37.1 22.6 51.7 #> PSD-P 19.0 7.2 30.9 #> PSD-M 7.6 0.0 15.6 #> PSD-T 1.0 0.0 3.9 #> PSD S-Q 62.9 48.3 77.4 #> PSD Q-P 18.1 6.5 29.7 #> PSD P-M 11.4 1.9 21.0 #> PSD M-T 6.7 0.0 14.2psdCalc(~yepmm,data=yepdf,species="Yellow perch",digits=1,drop0Est=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-Q 37.1 22.6 51.7 #> PSD-P 19.0 7.2 30.9 #> PSD-M 7.6 0.0 15.6 #> PSD-T 1.0 0.0 3.9 #> PSD S-Q 62.9 48.3 77.4 #> PSD Q-P 18.1 6.5 29.7 #> PSD P-M 11.4 1.9 21.0 #> PSD M-T 6.7 0.0 14.2## add a length psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=150)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-150 70 56 85 #> PSD-Q 37 21 53 #> PSD-P 19 6 32 #> PSD-M 8 0 16 #> PSD-T 1 0 4 #> PSD S-150 30 15 44 #> PSD 150-Q 33 18 49 #> PSD Q-P 18 6 31 #> PSD P-M 11 1 22 #> PSD M-T 7 0 15## add lengths with names psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=150,addNames="minLen")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minLen 70 56 85 #> PSD-Q 37 21 53 #> PSD-P 19 6 32 #> PSD-M 8 0 16 #> PSD-T 1 0 4 #> PSD S-minLen 30 15 44 #> PSD minLen-Q 33 18 49 #> PSD Q-P 18 6 31 #> PSD P-M 11 1 22 #> PSD M-T 7 0 15psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c("minLen"=150))#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minLen 70 56 85 #> PSD-Q 37 21 53 #> PSD-P 19 6 32 #> PSD-M 8 0 16 #> PSD-T 1 0 4 #> PSD S-minLen 30 15 44 #> PSD minLen-Q 33 18 49 #> PSD Q-P 18 6 31 #> PSD P-M 11 1 22 #> PSD M-T 7 0 15psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c(150,275),addNames=c("minSlot","maxSlot"))#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minSlot 70 55 86 #> PSD-Q 37 20 54 #> PSD-P 19 5 33 #> PSD-maxSlot 15 3 28 #> PSD-M 8 0 17 #> PSD-T 1 0 4 #> PSD S-minSlot 30 14 45 #> PSD minSlot-Q 33 17 50 #> PSD Q-P 18 5 31 #> PSD P-maxSlot 4 0 10 #> PSD maxSlot-M 8 0 17 #> PSD M-T 7 0 15psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c("minLen"=150,"maxslot"=275))#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minLen 70 55 86 #> PSD-Q 37 20 54 #> PSD-P 19 5 33 #> PSD-maxslot 15 3 28 #> PSD-M 8 0 17 #> PSD-T 1 0 4 #> PSD S-minLen 30 14 45 #> PSD minLen-Q 33 17 50 #> PSD Q-P 18 5 31 #> PSD P-maxslot 4 0 10 #> PSD maxslot-M 8 0 17 #> PSD M-T 7 0 15## add lengths with names, return just those values that use those lengths psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c("minLen"=150),justAdds=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minLen 70 56 85 #> PSD S-minLen 30 15 44 #> PSD minLen-Q 33 18 49psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c("minLen"=150),justAdds=TRUE, what="traditional")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> 70 56 85psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c(150,275), addNames=c("minSlot","maxSlot"),justAdds=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minSlot 70 55 86 #> PSD-maxSlot 15 3 28 #> PSD S-minSlot 30 14 45 #> PSD minSlot-Q 33 17 50 #> PSD P-maxSlot 4 0 10 #> PSD maxSlot-M 8 0 17psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=c(150,275), addNames=c("minSlot","maxSlot"),justAdds=TRUE,what="traditional")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-minSlot 70 55 86 #> PSD-maxSlot 15 3 28## different output types psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=150,what="traditional")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-150 70 56 85 #> PSD-Q 37 21 53 #> PSD-P 19 6 32 #> PSD-M 8 0 16 #> PSD-T 1 0 4psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=150,what="incremental")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD S-150 30 15 44 #> PSD 150-Q 33 18 49 #> PSD Q-P 18 6 31 #> PSD P-M 11 1 22 #> PSD M-T 7 0 15psdCalc(~yepmm,data=yepdf,species="Yellow perch",addLens=150,what="none")#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.## Show intermediate values psdCalc(~yepmm,data=yepdf,species="Yellow perch",showInterm=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> num stock Estimate 95% LCI 95% UCI #> PSD-Q 39 105 37 23 52 #> PSD-P 20 105 19 7 31 #> PSD-M 8 105 8 0 16 #> PSD-T 1 105 1 0 4 #> PSD S-Q 66 105 63 48 77 #> PSD Q-P 19 105 18 7 30 #> PSD P-M 12 105 11 2 21 #> PSD M-T 7 105 7 0 14psdCalc(~yepmm,data=yepdf,species="Yellow perch",what="traditional",showInterm=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> num stock Estimate 95% LCI 95% UCI #> PSD-Q 39 105 37 23 52 #> PSD-P 20 105 19 7 31 #> PSD-M 8 105 8 0 16 #> PSD-T 1 105 1 0 4psdCalc(~yepmm,data=yepdf,species="Yellow perch",what="incremental",showInterm=TRUE)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> num stock Estimate 95% LCI 95% UCI #> PSD S-Q 66 105 63 48 77 #> PSD Q-P 19 105 18 7 30 #> PSD P-M 12 105 11 2 21 #> PSD M-T 7 105 7 0 14## Control the digits psdCalc(~yepmm,data=yepdf,species="Yellow perch",digits=1)#> Warning: Some category sample size <20, some CI coverage may be #> lower than 95%.#> Estimate 95% LCI 95% UCI #> PSD-Q 37.1 22.6 51.7 #> PSD-P 19.0 7.2 30.9 #> PSD-M 7.6 0.0 15.6 #> PSD-T 1.0 0.0 3.9 #> PSD S-Q 62.9 48.3 77.4 #> PSD Q-P 18.1 6.5 29.7 #> PSD P-M 11.4 1.9 21.0 #> PSD M-T 6.7 0.0 14.2