simulate1

Simulated data from a completely randomized experiment with multiple assessments over time

datasets

Performs the analysis of completely randomized experimental designs (CRD), randomized blocks (RBD) and Latin square (LSD), experiments in double and triple factorial scheme (in CRD and RBD), experiments in subdivided plot scheme (in CRD and RBD), subdivided and joint analysis of experiments in CRD and RBD, linear regression analysis, test for two samples. The package performs analysis of variance, ANOVA assumptions and multiple comparison test of means or regression, according to Pimentel-Gomes (2009, ISBN: 978-85-7133-055-9), nonparametric test (Conover, 1999, ISBN: 0471160687), test for two samples, joint analysis of experiments according to Ferreira (2018, ISBN: 978-85-7269-566-4) and generalized linear model (glm) for binomial and Poisson family in CRD and RBD (Carvalho, FJ (2019), <doi:10.14393/ufu.te.2019.1244>). It can also be used to obtain descriptive measures and graphics, in addition to correlations and creative graphics used in agricultural sciences (Agronomy, Zootechnics, Food Science and related areas).

Gabriel Danilo Shimizu

AgroR

Experimental Statistics and Graphics for Agricultural Sciences

Rodrigo Yudi Palhaci Marubayashi

Leandro Simoes Azeredo Goncalves

simulate1 function

data.frame containing data set<dl>
 <dt><code>tempo</code></dt>
<dd>Categorical vector with time</dd> <dt><code>trat</code></dt>
<dd>Categorical vector with treatment</dd> <dt><code>resp</code></dt>
<dd>Categorical vector with response</dd> 
</dl>

Format

Dataset: Simulated data dict — simulate1

data.frame containing data set<dl>
 <dt><code>tempo</code></dt>
<dd>Categorical vector with time</dd>

 <dt><code>trat</code></dt>
<dd>Categorical vector with treatment</dd>

 <dt><code>resp</code></dt>
<dd>Categorical vector with response</dd>

 
</dl>

simulate1: Dataset: Simulated data dict

Description

Usage

Arguments

Format

See Also

Examples