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
)
```

### 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 ("mean_sd") or mean with standard error (default - "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

### 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)