This is a function of the bar graph for one factor with facets

barfacet(
  model,
  facet = NULL,
  theme = theme_bw(),
  geom = "bar",
  fill = "lightblue",
  pointsize = 4.5,
  width.bar = 0.15
)

Arguments

model

DIC, DBC or DQL object

facet

vector with facets

theme

ggplot2 theme

geom

graph type (columns or segments)

fill

fill bars

pointsize

Point size

width.bar

width of the error bars of a regression graph.

Value

Returns a bar chart for one factor

Author

Gabriel Danilo Shimizu, shimizu@uel.br

Leandro Simoes Azeredo Goncalves

Rodrigo Yudi Palhaci Marubayashi

Examples

library(AgroR)
data("laranja")
a=with(laranja, DBC(trat, bloco, resp,
     mcomp = "sk",angle=45,
     ylab = "Number of fruits/plants"))
#> 
#> -----------------------------------------------------------------
#> Normality of errors
#> -----------------------------------------------------------------
#>                          Method Statistic  p.value
#>  Shapiro-Wilk normality test(W) 0.9475889 0.187264
#> 
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, errors can be considered normal
#> 
#> -----------------------------------------------------------------
#> Homogeneity of Variances
#> -----------------------------------------------------------------
#>                               Method Statistic p.value
#>  Bartlett test(Bartlett's K-squared)  4.036888 0.85378
#> 
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, the variances can be considered homogeneous
#> 
#> -----------------------------------------------------------------
#> Independence from errors
#> -----------------------------------------------------------------
#>                  Method Statistic   p.value
#>  Durbin-Watson test(DW)  2.324604 0.2484349
#> 
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, errors can be considered independent
#> 
#> -----------------------------------------------------------------
#> Additional Information
#> -----------------------------------------------------------------
#> 
#> CV (%) =  8.69
#> MStrat/MST =  0.91
#> Mean =  182.5556
#> Median =  183
#> Possible outliers =  No discrepant point
#> 
#> -----------------------------------------------------------------
#> Analysis of Variance
#> -----------------------------------------------------------------
#>           Df      Sum Sq    Mean.Sq     F value        Pr(F)
#> trat       8 22981.33333 2872.66667 11.41142069 2.636524e-05
#> bloco      2    33.55556   16.77778  0.06664828 9.357825e-01
#> Residuals 16  4027.77778  251.73611                         
#> 
#> As the calculated p-value, it is less than the 5% significance level. The hypothesis H0 of equality of means is rejected. Therefore, at least two treatments differ

#> 
#> -----------------------------------------------------------------
#> Multiple Comparison Test
#> -----------------------------------------------------------------
#>                      resp groups
#> Country orange   250.3333      a
#> NRL              193.3333      b
#> FRL              192.3333      b
#> Cleopatra        183.6667      b
#> Clove Lemon      182.3333      b
#> Clove Tangerine  180.3333      b
#> Citranger-troyer 165.3333      c
#> Sunki            155.3333      c
#> Trifoliata       140.0000      c
#> 

barfacet(a,c("S1","S1","S1","S1","S1",
             "S2","S2","S3","S3"))