quant.fat2.desd {AgroR}

Analysis: Polynomial splitting for double factorial in DIC and DBC

Description

Splitting in polynomials for double factorial in DIC and DBC. Note that f1 must always be qualitative and f2 must always be quantitative. This function is an easier way to visualize trends for dual factor schemes with a quantitative and a qualitative factor.

Usage

quant.fat2.desd(factors = list(f1, f2, block), response, dec = 3)

Arguments

factors

Define f1 and f2 and/or block factors in list form. Please note that in the list it is necessary to write 'f1', 'f2' and 'block'. See example.

response

response variable

dec

Number of cells

Value

Returns the coefficients of the linear, quadratic and cubic models, the p-values of the t test for each coefficient (p.value.test) and the p-values for the linear, quadratic, cubic model splits and the regression deviations.

Author(s)

Gabriel Danilo Shimizu, [e-mail]

See Also

FAT2DIC, FAT2DBC

Examples

library(AgroR)
data(cloro)
quant.fat2.desd(factors = list(f1=cloro$f1,
f2=rep(c(1:4),e=5,2), block=cloro$bloco),
response=cloro$resp)