This is a function of the bar graph for one factor

bar_graph(model, fill = "lightblue", horiz = TRUE)

Arguments

model

DIC, DBC or DQL object

fill

fill bars

horiz

Horizontal Column (default is TRUE)

Value

Returns a bar chart for one factor

Author

Gabriel Danilo Shimizu, shimizu@uel.br

Leandro Simoes Azeredo Goncalves

Rodrigo Yudi Palhaci Marubayashi

Examples

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: Scott-Knott
#> -----------------------------------------------------------------
#>                      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
#> 

bar_graph(a,horiz = FALSE)