Reference

Shimizu, G. D. Gonçalves, L. S. A. AgroReg: Regression Analysis Linear and Nonlinear for Agriculture. (2022). R package version 1.2.1. Disponível em: https://cran.r-project.org/web/packages/AgroReg/index.html




The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable





















Graphics parameters





          
The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable






















Graphics parameters




The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable















The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable





























Graphics parameters


          
The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable







                      
























Graphics parameters





          
The Shiny AgroReg App allows the entry of data in .csv extension (Separated by comma, period or semi-colon), .xls or .xlsx
Note. The tabulation of data must be done in columns, each one being represented by a factor or response variable









Note: Note that the ED, DL or EC is based on the highest response value for Y and not necessarily the 100% value










In case of estimating a lethal dose value disregarding the upper limit of the curve, use the option below. Note that it is necessary to simulate data to obtain an approximate value. Use rounding and increase the number of simulations for better precision











Graphics parameters