[R] Bayes Factor

[James Henson]

Hello R Community,
Subject: Bayes Factor
A Bayesian ANOVA of the form:
competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition)
Returns the following Error message:
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘compare’ for
signature ‘"BFlinearModel", "missing", "tbl_df"’

My guess the problem is in the ‘class’, which is:
[1] “tbl_df”  “tbl”  “data.frame”
The data was imported via the ‘readr’ package through R Studio, and
then saved as a RData file.
My code is below, and the data is attached as a text file.

Thanks for your assistance.
Best regards,
James

# Plots for Interpreting One-Way ANOVA

library(digest)

library(DT)

datatable(competition)

# Characterize the data.

class(competition)

str(competition)

competition$clipping <- as.factor(competition$clipping)

competition$biomass <- as.numeric(competition$biomass)

str(competition)

#

tapply(competition$biomass, competition$clipping, mean)

tapply(competition$biomass, competition$clipping, sd)





# Bayesian Procedure for ANOVA



# Calculate Bayes Factors

library(BayesFactor)

competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition)

# Run mcmc iterations

mcmcOut2 <- posterior(competitionBayesOut, iterations = 10000)

# boxplot of the posteriors for the groups

boxplot(as.matrix(mcmcOut2[,2:6]))

# Show the HDIs

summary(mcmcOut2)

# Calculate the Bayes Factor

competitionBayesOut



# Pairwise "post hoc" tests

library(rjags)

library(BEST)



# competitionare 'r5' vs. 'control'

plot(BESTmcmc(competition[competition$clpping=="r5",2],
competition[competition$clipping=="control",2]))

#

plot(BESTmcmc(competition[competition$clpping=="r10",2],
competition[competition$clipping=="control",2]))

# competitionare 'n10' vs. 'control'

plot(BESTmcmc(competition[competition$clipping=="n10",2],
competition[competition$clipping=="control",2]))

# competitionare 'n50' vs. 'control'

plot(BESTmcmc(competition[competition$clipping=="n50",2],
competition[competition$clipping=="control",2]))
-------------- next part --------------
clipping	biomass
n25	551
n25	457
n25	450
n25	731
n25	499
n25	632
n50	595
n50	580
n50	508
n50	583
n50	633
n50	517
r5	639
r5	615
r5	511
r5	573
r5	648
r5	677
control	417
control	449
control	517
control	438
control	415
control	555
r10	563
r10	631
r10	522
r10	613
r10	656
r10	679