Internal Noise

data = read.csv('Recovered_Parameters/Internal/InternalNoise_Summary.csv')
converge = read.csv('Recovered_Parameters/Internal/InternalNoise_Convergence.csv')
converge$converged = "No"
converge$converged[converge$Rhat_k < 1.2 & converge$Rhat_l < 1.2 & converge$Rhat_s < 1.2] = 'Yes'

message(paste('Percent Chains Converged:', 100*dim(converge[converge$converged=='Yes',])[1] / dim(converge)[1]))
## Percent Chains Converged: 100
data$PercentVar = mapvalues(data$PercentVar, 
                            from = c('Var_001', 'Var_01', 'Var_05',
                                     'Var_10', 'Var_25'),
                            to = c('0.1%', '1%', '5%',
                                     '10%', '25%'))

data = subset(data, PercentVar %in% c('0.1%', '1%', '5%'))

Recovered Number of ELIs: k

ggplot(data, aes(PercentVar, k_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=10), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab('Recovered k') +
  scale_y_continuous(breaks=seq(0, 12, 2)) +
  theme_bw()

Recovered Rate of ELIs: \(\lambda\)

ggplot(data, aes(PercentVar, lambda_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=0.5), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab(expression(paste('Recovered ',lambda))) +
  scale_y_continuous(breaks=seq(0, 0.6, 0.1)) +
  theme_bw()

Recovered Start Time: s

ggplot(data, aes(PercentVar, start_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=4), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab('Recovered start time') +
  scale_y_continuous(breaks=seq(0, 14, 2)) +
  theme_bw()

External Noise

data = read.csv('Recovered_Parameters/External/ExternalNoise_Summary.csv')
converge = read.csv('Recovered_Parameters/External/ExternalNoise_Convergence.csv')
converge$converged = "No"
converge$converged[converge$Rhat_k < 1.2 & converge$Rhat_l < 1.2 & converge$Rhat_s < 1.2] = 'Yes'

message(paste('Percent Chains Converged:', 100*dim(converge[converge$converged=='Yes',])[1] / dim(converge)[1]))
## Percent Chains Converged: 100
data$PercentVar = mapvalues(data$PercentVar, 
                            from = c('Var_001', 'Var_01', 'Var_05',
                                     'Var_10', 'Var_25'),
                            to = c('0.1%', '1%', '5%',
                                     '10%', '25%'))

Recovered Number of ELIs: k

ggplot(data, aes(PercentVar, k_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=10), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab('Recovered k') +
  scale_y_continuous(breaks=seq(0, 12, 2)) +
  theme_bw()

Recovered Rate of ELIs: \(\lambda\)

ggplot(data, aes(PercentVar, lambda_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=0.5), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab(expression(paste('Recovered ',lambda))) +
  scale_y_continuous(breaks=seq(0, 0.6, 0.1)) +
  theme_bw()

Recovered Start Time: s

ggplot(data, aes(PercentVar, start_Mean, fill=PercentVar)) +
  stat_summary(fun.y=mean, geom='bar') +
  stat_summary(fun.data=mean_cl_boot, geom='linerange') +
  geom_hline(aes(yintercept=4), linetype=2) +
  xlab('Percent Variance Added') +
  guides(fill=F) +
  ylab('Recovered start time') +
  scale_y_continuous(breaks=seq(0, 14, 2)) +
  theme_bw()