Articles by fishR Blog

Replace filterD()

May 25, 2021 | fishR Blog

We are deprecating filterD() from the next version of FSA (v0.9.0). It will likely be removed by the start of 2022. filterD() was an attempt to streamline the process of using filter() (from dplyr) followed by droplevels() to remove levels ... [Read more...]

Replace fitPlot() with ggplot

May 24, 2021 | fishR Blog

Introduction We are deprecating fitPlot() from the next version of FSA (v0.9.0). It will likely be removed at the end of the year 2001. We are taking this action to make FSA more focused on fisheries applications and to eliminate “black box... [Read more...]

Replace compIntercepts() with emmeans()

May 11, 2021 | fishR Blog

Introduction The compIntercepts() function in FSA (prior to v0.9.0) was used to statistically compare intercepts for all pairs of groups with the same slope in an indicator/dummy variable regression (I/DVR). However, the excellent emmeans()... [Read more...]

Replace compSlopes() with emtrends()

May 10, 2021 | fishR Blog

Introduction The compSlopes() function in FSA (prior to v0.9.0) was used to statistically compare slopes for all pairs of groups in an indicator/dummy variable regression (I/DVR). However, the excellent emtrends() function in the emmmeans p... [Read more...]

Age Bias Plots Using ggplot

March 14, 2021 | fishR Blog

Guest Post Note Please note that this is a guest post to fishR by Michael Lant, who at the time of this writing is a Senior at Northland College. Thanks, Michael, for the contribution to fishR.   Introduction My objective is to demonstrate ... [Read more...]

von Bertalanffy Growth Plots II

January 2, 2020 | fishR Blog

Introduction library(FSAdata) # for data library(FSA) # for vbFuns(), vbStarts(), confint.bootCase() library(car) # for Boot() library(dplyr) # for filter(), mutate() library(ggplot2)In a previous post I demonstrated how to make a plot that illustrated the fit of a von Bertalanffy growth function (VBGF) to data. In this post, ... [Read more...]

von Bertalanffy Growth Plots I

December 31, 2019 | fishR Blog

Introduction library(FSAdata) # for data library(FSA) # for vbFuns(), vbStarts(), confint.bootCase() library(car) # for Boot() library(dplyr) # for filter(), mutate() library(ggplot2)I am continuing to learn ggplot2 for elegant graphics. I often make a plot to illustrate the fit of a von Bertalanffy growth function to data. In ... [Read more...]

RFishBC CRAN Release

November 22, 2018 | fishR Blog

I am pleased to announce that the RFishBC package has been released to CRAN. This package is intended to help fisheries scientists gather age and measurement data from digital images of calcified structures and, possibly, back-calculate p... [Read more...]

New FSA Authors

November 3, 2018 | fishR Blog

It was always my hope that the Fisheries Stock Assessment (FSA) R package would become a community endeavor. With the recent release on CRAN of v0.8.21 that hope has finally come to fruition. This version has two new co-authors. Alexis Din... [Read more...]

Testers for RFishBC

June 6, 2018 | fishR Blog

Back-calculating lengths of fish at previous ages from measurements made on calcified structures (scales, otoliths, etc.) is fairly common practice within some fisheries agencies and institutions. The FishBC software distributed by the Amer... [Read more...]

Adding Zero Catches

April 18, 2018 | fishR Blog

Introduction Much of my work is with undergraduates who are first learning to analyze fisheries data. A common “learning opportunity” occurs when students are asked to compute the mean catch (or CPE), along with a standard deviation (SD), across multiple gear sets for each species. The learning opportunity occurs because ... [Read more...]

Collapsing Categories or Values

March 29, 2018 | fishR Blog

Introduction I have received a few queries recently that can be categorized as “How do I collapse a list of categories or values into a shorter list of category or values?” For example, one user wanted to collapse species of fish into ... [Read more...]

Stock-Recruitment Graphing Questions

December 12, 2017 | fishR Blog

A fishR user recently asked me In the book that you published, I frequently use the stock-recruit curve code. The interface that shows both the Ricker/Beverton-Holt figure with the recruit per spawner to spawner figure (i.e., the dynamic ... [Read more...]

Plots of Back-Calculated Lengths-At-Age I

November 7, 2017 | fishR Blog

Last spring, I posted about my version of a modified age-bias plot. One reader commented on that post via Twitter – “Now that you solved the age-bias plot, how about the ‘best’ display of back-calculated length-at-age data, with Von... [Read more...]

Joy Plot of Length Frequencies

July 27, 2017 | fishR Blog

There has been a bit of a buzz recently about so-called “joyplots.” Wilke described joyplots as “partially overlapping line plots that create the impression of a mountain range.” I would describe them as partially overlapping densit... [Read more...]

Age Bias Plot Changes in FSA

April 25, 2017 | fishR Blog

In the last two weeks, I have posted twice about modifying age bias plots and Bland-Altman-like plots for comparing age estimates. From those posts, I have decided that I prefer to plot differences between the ages on the y-axis (as com... [Read more...]

Bland-Altman Plot for Age Comparisons?

April 19, 2017 | fishR Blog

Last week I posted about a modified age bias plot. In this post I began looking more deeply at an alternative plot called the Bland-Altman plot. Below, I describe this plot, demonstrate how to construct it in R, give a mild critique of its ... [Read more...]

Modified Age Bias Plot

April 13, 2017 | fishR Blog

Original Age Bias Plot Campana et al. (1995) introduced the “age bias plot” to visually assess potential differences in paired age estimates (e.g., between two structures such as scales and otoliths, between two readers, or between one ... [Read more...]

Computing SE for PSD indices

December 9, 2016 | fishR Blog

A user of my Introductory Fisheries Analyses with R book recently asked me how to compute standard errors (SE) for the various PSD indices by using the usual equation for the SE of a proportion (square root of p times (1-p) divided by n). B... [Read more...]
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