update function names, harmonize terminology

README.md

@@ -2,23 +2,23 @@
 
 ## Authors/developers: Christie A. Bahlai [@cbahlai](https://github.com/cbahlai) and Elise F. Zipkin [@ezipkin](https://github.com/ezipkin)
 
-In this repository, we develop a novel break-point analysis tool for population time series data, building on the methods described in [Bahlai et al 2015, Ecological Applications](https://doi.org/10.1890/14-2022.1). The tool uses the Ricker model as the data-generating process for a dynamic regime, iterates through all break point combinations, and uses information-theoretic decision tools (i.e. Akaike's Information Criteron) to determine best fits. In this repository we develop the tool, simulate data under a variety of conditions to demonstrate the tool, and apply the tool to two case studies: overwintering populations of monarch butterflies and invasions of multicolored Asian ladybeetle. This tool is scripted entirely in R.
+In this repository, we develop a novel break-point analysis tool for population time series data, building on the methods described in [Bahlai et al 2015, Ecological Applications](https://doi.org/10.1890/14-2022.1). The tool uses the Ricker model as the data-generating process for a dynamic rule, iterates through all break point combinations, and uses information-theoretic decision tools (i.e. Akaike's Information Criteron) to determine best fits. In this repository we develop the tool, simulate data under a variety of conditions to demonstrate the tool, and apply the tool to two case studies: overwintering populations of monarch butterflies and invasions of multicolored Asian ladybeetle. This tool is scripted entirely in R.
 
 ## File navigation
 
-**regime_shift_detector.R** - contains functions to detect regime shifts in population time series. The function RSdetector() takes raw time series data and generates a complete report on fits, best fits, break points, and regression parameters for models with best fits
+**dynamic_shift_detector.R** - contains functions to detect regime shifts in population time series. The function DSdetector() takes raw time series data and generates a complete report on fits, best fits, break points, and regression parameters for models with best fits
 
-**monarch_example.R** - applies the regime shift detector analysis to monarch overwintering data from Mexico
+**monarch_example.R** - applies the dynamic shift detector analysis to monarch overwintering data from Mexico
 
 **plot_monarch_figures.R** - plots output from monarch example, places outputs in **figs folder**
 
-**harmonia_example.R** - applies the regime shift detector analysis to harmonia ladybeetle population data from Kellogg Biological Station. Includes data cleaning/manipulation code after Bahlai et al 2015.
+**harmonia_example.R** - applies the dynamic shift detector analysis to harmonia ladybeetle population data from Kellogg Biological Station. Includes data cleaning/manipulation code after Bahlai et al 2015.
 
 **plot_harmona_figures.R** - plots output from harmonia example, places outputs in **figs folder**
 
-**simulations.R**- a set of functions that creates time series data using secified parameters, and then a set of funtions to test if the parameters input match the ones detected by the regime shift detector, and the code that creates simulations under a variety of conditions, runs it through the comparison functions, and tallies the outputs, outputs a CSV file to the **'simresults' folder**
+**simulations.R**- a set of functions that creates time series data using secified parameters, and then a set of funtions to test if the parameters input match the ones detected by the dynamic shift detector, and the code that creates simulations under a variety of conditions, runs it through the comparison functions, and tallies the outputs, outputs a CSV file to the **'simresults' folder**
 
-**plot_simulation_results.R** - takes the simulation outputs and creates plots based on varying one input at a time to see the RSdetector's performance under differing conditions- outputs figures as PDF vector graphis to the **'figs' folder**
+**plot_simulation_results.R** - takes the simulation outputs and creates plots based on varying one input at a time to see the DSdetector's performance under differing conditions- outputs figures as PDF vector graphis to the **'figs' folder**
 
 **casestudydata folder** contains data for Harmonia case study. Monarch study data are proprietary