polynomial2 {AgroR} R Documentation

## Analysis: Linear regression graph in double factorial

### Description

Linear regression analysis for significant interaction of an experiment with two factors, one quantitative and one qualitative

### Usage

polynomial2(
fator1,
resp,
fator2,
color = NA,
grau = NA,
ylab = "Response",
xlab = "Independent",
theme = theme_classic(),
se = FALSE,
point = "mean_sd",
legend.title = "Treatments",
posi = "top",
textsize = 12,
ylim = NA,
family = "sans",
width.bar = NA,
pointsize = 3,
linesize = 0.8,
separate = c("(\"", "\")"),
n = NA,
DFres = NA,
SSq = NA
)


### Arguments

 fator1 Numeric or complex vector with factor 1 levels resp Numerical vector containing the response of the experiment. fator2 Numeric or complex vector with factor 2 levels color Graph color (default is NA) grau Degree of the polynomial (1,2 or 3) ylab Dependent variable name (Accepts the expression() function) xlab Independent variable name (Accepts the expression() function) theme ggplot2 theme (default is theme_classic()) se Adds confidence interval (default is FALSE) point Defines whether to plot all points ("all"), mean ("mean"), mean with standard deviation (default - "mean_sd") or mean with standard error ("mean_se"). legend.title Title legend posi Legend position textsize Font size (default is 12) ylim y-axis scale family Font family (default is sans) width.bar width of the error bars of a regression graph. pointsize Point size (default is 4) linesize line size (Trendline and Error Bar) separate Separation between treatment and equation (default is c("(\"","\")")) n Number of decimal places for regression equations DFres Residue freedom degrees SSq Sum of squares of the residue

### Value

Returns two or more linear, quadratic or cubic regression analyzes.

### Author(s)

Gabriel Danilo Shimizu, shimizu@uel.br

Leandro Simoes Azeredo Goncalves

Rodrigo Yudi Palhaci Marubayashi

dose=rep(c(0,0,0,2,2,2,4,4,4,6,6,6),3)