Post script Appendix
This notebook is a post script appendix to the paper
- Aki Vehtari, Andrew Gelman, Daniel Simpson, Bob Carpenter, Paul-Christian Bürkner (2021): Rank-normalization, folding, and localization: An improved \(\widehat{R}\) for assessing convergence of MCMC. Bayesian analysis, 16(2):667-718. doi:10.1214/20-BA1221.
The code used to make this notebook is available at https://github.com/avehtari/rhat_ess.
Introduction
The MCMC effective sample size (ESS) and Monte Carlo standard error (MCSE) estimated for one chain includes estimation of the correlation between the iterations, for example, using autocorrelation time (or spectral density at frequency zero). As a finite number of MCMC draws are available the autocorrelation estimates for bigger lags are noisier. In the paper, we wrote about autocorrelation estimators
In our experiments, Geyer’s [(1992)] truncation had superior stability compared to flat-top (Doss et al., 2014) and slug-sail (Vats and Knudson, 2018) lag window approaches.
(Vats and Knudson (2018) has since been published as Vats and Knudson (2021)). As the main point of the paper was not comparison of autocorrelation estimators, the experimental results were not included in the paper.
This notebook includes additional experiments comparing the Geyer’s (1992) truncation approach to three other methods for estimating effective sample size (ESS) and corresponding Monte Carlo standard error (MCSE). We also compare the new quantile MCSE method we proposed in the paper (Vehtari et al., 2021) to batch means quantile MCSE method by (Gong and Flegal, 2015). Finally, we compare the behavior of ESS implementations in four R packages in case of multiple chains and well separated multimodal distribution.
The methods and R packages compared
stableGR
(n.eff
) computes a weighted sum of autocorrelations using slug-sail lag window (Vats and Knudson, 2018)
- ‘mcmcse’ (
ess
and mcse.q
) uses by default a batch means approach (Gong and Flegal, 2015)
coda
(effectiveSize
) computes the spectral density at frequency zero by fitting an AR model to the chain (Heidelberger and Welch, 1981)
posterior
: ess_basic
computes sum of autocorrelations using Geyer’s truncation rule (Geyer, 1992), and mcse_quantile
uses in addition an inverse approach for quantile MCSE. The posterior
package also takes into account the the possibility that the chains are not mixing by using also multi-chain \(\widehat{R}\) in ESS and MCSE computations.
tl;dr
In case of well mixing chains, ess_basic
and mcse_quantile
in the posterior
package are the most accurate methods. In case of well separated modes, the posterior
package also provides appropriately small ESS indicating that the chains are not mixing.
Comparison of ESS estimators with AR(1) simulation
Mean of x
We simulate \(M=4\) chains from a known AR(1) process with varying parameter \(\phi\), and normal(0,1) marginal distribution.
x1 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x2 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x3 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x4 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
We vary the length of the chains, \(N\), and the AR process parameter \(\phi\)
Ns=c(100, 1000, 10000)
phis=c(-0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9)
\(N=1000\) is the default in Stan, and \(N=100\) and \(N=10000\) are used to illustrate the behavior with less or more MCMC iterations. The total number of draws is \(S=M*N\).
The values of \(\phi\) have been chosen to reflect typical ESS/\(S\) values seen from Stan. The chosen \(\phi\) values correspond to ESS/\(S\) values \((1.9, 1.2, 0.8, 0.5, 0.3, 0.2, 0.1)\). The two first \(\phi\) values being negative produce antithetic chains with ESS>\(S\), which is not rare when using Stan’s dynamic Hamiltonian Monte Carlo.
Simulation is repeated \(100\,000\) times for each combination of \(N\) and \(\phi\). For each simulation we compute the empirical mean. The variance of the empirical means and known true variance are used to compute the asymptotic efficiency, that is, true ESS/\(S\) when \(S\rightarrow \infty\). For each simulation we compute three ESS estimates and use those to compute Monte Carlo standard error (MCSE) which is compared to the actual error, that is, the difference between the empirical mean \(\hat{\mu}\) and known true mean \(\mu=0\).
The following figure summarizes the results. In the case of estimating some posterior expectation \(\mathrm{E}[g(x)]\), the used ESS estimators assume finite variance and MCSE is simply \(\mathrm{sd}[g(x)]/\sqrt{\mathrm{ESS}}\). Thus accuracy of ESS is directly related to the accuracy of MCSE. We report root mean square of standardized errors \(|\mu - \hat{\mu}|/\widehat{\mathrm{MCSE}}\), which is in case of well calibrated ESS and MCSE should be close to 1. Values less than 1 indicate underestimated ESS and overestimated MCSE, and values larger than 1 indicate overestimated ESS and underestimated MCSE.
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posterior: Geyer
is on average clearly closer to 1 than the other methods. coda: AR
method is overconfident with short chains, but has good behavior with longer chains. stableGR: Slug-sail
has quite unpredictable behavior being either over- or underconfident, except in case of very long chains when the method is consistently overconfident for antithetic chains and underconfident for “thetic” chains. Not shown in the plot, but slug-sail estimator had overall much higher variance than Geyer’s and AR approaches.
Although the differences between methods are clear, the effect of using the methods with bigger errors is likely to be small in most actual Bayesian modeling use cases. Except for the shortest chains with the highest autocorrelations, the errors in MCSE are at highest 20%, which should provide sufficient information whether more draws are needed. With more draws the accuracy of all methods improve.
Mean of x^2
In the above the chains were simulated from AR(1) process, so we would expect that coda: AR
method would have some advantage. Also the chains have normal(0,1) marginal which makes the empirical means also to behave nicely. As an alternative we test the methods also with the same AR processes, but values are squared so that the chains are non-linear transformation of the AR process and the marginal is skewed. Squared variable is, for example, a natural part of variance computation.
x1 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x2 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x3 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x4 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
The chosen \(\phi\) values correspond to now ESS/\(S\) values \((0.8, 1.0, 1.0, 0.8, 0.6, 0.3, 0.1)\). The squaring breaks the antithetic behavior, but for simplicity we show the results for all different values of \(\phi\).
![](data:image/png;base64,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Again posterior: Geyer
is on average clearly closer to 1 than the other methods. All methods have bigger errors for the short chains (S=4 x 100), especially when ESS/\(S\) is small, which is natural as the draws are from a skewed distribution and the variability in means and correlations increases. With increasing number of draws the error decreases for all methods.
Probability p(x<0)
Next we examine the behavior for estimating probabilities. The sequence is now binary with values 0 and 1, computed with an indicator function I(x<0).
x1 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x2 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x3 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x4 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
The chosen \(\phi\) values correspond to now ESS/\(S\) values \((1.4, 1.1, 0.9, 0.6, 0.4, 0.2, 0.1)\). We see super-efficiency for antithetic chains.
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Again posterior: Geyer
is on average clearly closer to 1 than the other methods. All methods have bigger errors for the short chains (S=4 x 100), especially when ESS/\(S\) is small, which is natural as binary observation contain less information than continuous observations. With increasing number of draws the error decreases for all methods.
Comparison of ESS estimators for bimodal distribution
Above, AR process was used to simulate MCMC sampling from a unimodal distribution. We advocate running many chains not just for the parallelization of the computation, but also to be able to detect possible multimodality. Here we sample from a bimodal distribution using Stan. We vary the number of chains and examine the behavior of the ESS estimators in the same three packages.
posterior
package is the only one of these packages taking into account the the possibility that the chains are not mixing by using also multi-chain in ESS and MCSE computations. stableGR
and coda
accept multiple chains as input, but don’t show in ESS estimates indication of between chain mixing problems. mcmcse
accepts only one chain as input, and multiple chains were simply concatenated to provide a “single” chain as input.
The model is a simple Student’s \(t_4\) distribution with unknown location and scale.
data {int<lower=0> N; vector[N] y }
parameters {real mu;}
model {mu ~ student_t(4, 0, 100); y ~ student_t(4, mu, 1);}
The data is generated from a bimodal distribution.
N=20; y=c(rnorm(N/2, mean=-5, sd=1),rnorm(N/2, mean=5, sd=1));
With this data, the posterior is bimodal with well separated modes. The modes don’t necessarily have equal posterior mass. Stan’s dynamic HMC is not able to jump from one mode to another. The random initialization determines to which mode each chain ends up, and it is not possible to infer the actual relative posterior masses from the chains. The number of chains in each mode is random, and the probability of a chain with random initialization ending to a mode depends on the volume of the attraction area of that mode. In such case we would like to get a warning that the chains are not mixing.
The following plot shows an example of trace plot when one chain is stuck in one mode and three in another mode.
![](data:image/png;base64,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If we would repeat the sampling with random initializations and four chains, we would observe 0–4 chains stuck in one mode and the rest in the other mode. So there is still a possibility that all the chains are stuck in one mode and we think that the posterior is unimodal. With just one chain, we have probability of 0 recognizing that there are well separated modes. With more chains, it is possible that our random initialization is within the attraction area of just one mode, and then having more chains doesn’t help. In general, with increasing number of chains, we have higher probability of seeing more than one mode.
How should ESS estimates look like when we have chains that are not mixing? If the modes are well separated so that between-chain variance is much bigger than within-chain variances, each chain is mostly indicating the loaction of the mode and not worth much more than one observation. The posterior
package combines Geyer truncated autocorrelation estimates with multi-chain convergence diagnostic \(\widehat{R}\). If the chains are not mixing, then the draws within each chain are considered to be more correlated within the chain and the multi-chain ESS estimate gets smaller. If the modes are well separated, multi-chain ESS is close to the number of chains. Arguably even this is an overestimate as increasing the number of non-mixing chains does not provide reliable estimate of the relative masses of the masses.
The following plot shows ESS per chain estimates using the four packages and with increasing number of chains. Simulations have been repeated 100 times.
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With one chain, all packages consider only the within-chain correlation and report similar ESS per chain values (~350). When different chains end up to stuck in different well-separated modes, we would prefer to get an estimate that is indicating poor efficiency. With increasing number of chains, coda
keeps reporting similar ESS per chain (with less variation) and provides no indication of non-mixing chains. When at least on chain is stuck in a different mode, stableGR
reports ESS per chain of approximately 60, which is much less than 350, but we could see similar low values due to high autocorrelation and the total ESS is high enough not to indicate that chains are not mixing well. mcmcse
does not have support for multiple chains, but combining the chains to one chain, changes the autocorrelation estimate so that when the number of chains increases, eventually ESS per chain decreases close to 1, indicating inefficient sampling. posterior
reports ESS per chain close to 1 always when at least one chain is in the other mode, which is a clear indication that something is wrong in the mixing of the chains.
References
- Geyer, C. J. (1992). Practical Markov chain Monte Carlo. Statistical Science, 7:473–483.
- Gong, L., and Flegal, J. M. (2015). A practical sequential stopping rule for high-dimensional Markov chain Monte Carlo. Journal of Computational and Graphical Statistics, 25:684—700.
- Heidelberger, P., and Welch, P. D. (1981). A spectral method for confidence interval generation and run length control in simulations. Communications of the ACM, 24:233—245.
- Vats, D., and Knudson, C. (2018). Revisiting the Gelman-Rubin diagnostic. arXiv preprint, arXiv:1812.09384.
- Vats, D., and Knudson, C. (2021). Revisiting the Gelman-Rubin diagnostic. Statistical Science, 36(4): 518—529.
- Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., Bürkner, P.-C. (2021): Rank-normalization, folding, and localization: An improved \(\widehat{R}\) for assessing convergence of MCMC. Bayesian analysis, 16(2):667—718. doi:10.1214/20-BA1221.
---
title: "Comparison of MCMC effective sample size estimators"
author: "Aki Vehtari"
date: "First version 2021-11-03. Last modified `r format(Sys.Date())`."
output:
  html_document:
    theme: readable
    toc: true
    toc_depth: 3
    toc_float: true
    code_download: true
---

## Post script Appendix

This notebook is a post script appendix to the paper <br>

- Aki Vehtari, Andrew Gelman, Daniel Simpson, Bob Carpenter,
Paul-Christian Bürkner (2021): Rank-normalization, folding, and
localization: An improved $\widehat{R}$ for assessing convergence of MCMC. *Bayesian analysis*, 16(2):667-718. [doi:10.1214/20-BA1221](https://doi.org/10.1214/20-BA1221).

The code used to make this notebook is available at [https://github.com/avehtari/rhat_ess](https://github.com/avehtari/rhat_ess).

## Introduction

The MCMC effective sample size (ESS) and Monte Carlo standard error
(MCSE) estimated for one chain includes estimation of the
correlation between the iterations, for example, using
autocorrelation time (or spectral density at frequency zero). As a
finite number of MCMC draws are available the autocorrelation
estimates for bigger lags are noisier.  In the paper, we wrote
about autocorrelation estimators

> In our experiments, Geyer's [(1992)] truncation had superior
> stability compared to flat-top (Doss et al., 2014) and slug-sail
> (Vats and Knudson, 2018) lag window approaches.

(Vats and Knudson (2018) has since been published as Vats and
Knudson (2021)).  As the main point of the paper was not comparison
of autocorrelation estimators, the experimental results were not
included in the paper.

This notebook includes additional experiments comparing the Geyer's
(1992) truncation approach to three other methods for estimating
effective sample size (ESS) and corresponding Monte Carlo standard
error (MCSE). We also compare the new quantile MCSE method we
proposed in the paper (Vehtari et al., 2021) to batch means
quantile MCSE method by (Gong and Flegal, 2015). Finally, we
compare the behavior of ESS implementations in four R packages in
case of multiple chains and well separated multimodal distribution.

### The methods and R packages compared

- [`stableGR`](https://cran.r-project.org/package=stableGR) (`n.eff`) computes a weighted sum of autocorrelations using slug-sail lag window (Vats and Knudson, 2018) 
- ['mcmcse'](https://cran.r-project.org/package=mcmcse) (`ess` and `mcse.q`) uses by default a batch means approach (Gong and Flegal, 2015) 
- [`coda`](https://cran.r-project.org/package=coda) (`effectiveSize`) computes the spectral density at frequency zero by fitting an AR model to the chain (Heidelberger and Welch, 1981)
- [`posterior`](https://cran.r-project.org/package=posterior): `ess_basic` computes sum of autocorrelations using Geyer's truncation rule (Geyer, 1992), and `mcse_quantile` uses in addition an inverse approach for quantile MCSE. The `posterior` package also takes into account the the possibility that the chains are not mixing by using also multi-chain $\widehat{R}$ in ESS and MCSE computations.

### tl;dr

In case of well mixing chains, `ess_basic` and `mcse_quantile` in
the `posterior` package are the most accurate methods. In case of
well separated modes, the `posterior` package also provides
appropriately small ESS indicating that the chains are not mixing.


````{r setup, include=FALSE}
knitr::opts_chunk$set(message=FALSE, error=FALSE, warning=FALSE, comment=NA, cache=FALSE)
````
````{r load_packages, echo=FALSE}
library(tidyverse)
library(bayesplot)
theme_set(bayesplot::theme_default(base_family = "sans"))
library(khroma)
library(latex2exp)
````


## Comparison of ESS estimators with AR(1) simulation

### Mean of x

We simulate $M=4$ chains from a known AR(1) process with varying
parameter $\phi$, and normal(0,1) marginal distribution.
```
x1 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x2 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x3 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
x4 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)));
```

We vary the length of the chains, $N$, and the AR process parameter $\phi$
```
Ns=c(100, 1000, 10000)
phis=c(-0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9)
```

$N=1000$ is the default in Stan, and $N=100$ and $N=10000$ are used
to illustrate the behavior with less or more MCMC iterations. The
total number of draws is $S=M*N$.

The values of $\phi$ have been chosen to reflect typical ESS/$S$
values seen from Stan. The chosen $\phi$ values correspond to ESS/$S$
values $(1.9, 1.2, 0.8, 0.5, 0.3, 0.2, 0.1)$. The two first $\phi$
values being negative produce antithetic chains with ESS>$S$, which
is not rare when using Stan's dynamic Hamiltonian Monte Carlo.

Simulation is repeated $100\,000$ times for each combination of $N$
and $\phi$. For each simulation we compute the empirical mean. The
variance of the empirical means and known true variance are
used to compute the asymptotic efficiency, that is, true ESS/$S$ when
$S\rightarrow \infty$. For each simulation we compute three ESS
estimates and use those to compute Monte Carlo standard error
(MCSE) which is compared to the actual error, that is, the
difference between the empirical mean $\hat{\mu}$ and known true
mean $\mu=0$.

The following figure summarizes the results.  In the case of
estimating some posterior expectation $\mathrm{E}[g(x)]$, the used
ESS estimators assume finite variance and MCSE is simply
$\mathrm{sd}[g(x)]/\sqrt{\mathrm{ESS}}$. Thus accuracy of ESS is
directly related to the accuracy of MCSE. We report root mean
square of standardized errors $|\mu -
\hat{\mu}|/\widehat{\mathrm{MCSE}}$, which is in case of well calibrated ESS
and MCSE should be close to 1. Values less than 1 indicate
underestimated ESS and overestimated MCSE, and values larger than 1
indicate overestimated ESS and underestimated MCSE.


````{r plot1, echo=FALSE, fig.dim=c(9,3)}
load('ess_ar_df.Rdata')
Ns=c(100, 1000, 10000)
phis=c(-0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9)
ggplot(df, aes(x=phi, y=z, 
               group=method,
               color=method)) +
  geom_line(alpha=0.8, size=1) +
  geom_hline(yintercept = 1, linetype='dashed') +
  coord_cartesian(ylim=c(0.91,1.3), clip='off')+
  labs(x='True ESS/S', y=TeX('RMS of $|\\mu -\\hat{\\mu}| / \\widehat{MCSE}$'))+
  guides(linetype = guide_legend(title = "N"),
         color = guide_legend(title = "Package: Method"))+
  scale_x_continuous(breaks=phis, labels = round(tess/40000,1))+
  scale_color_bright(breaks=c("stableGR::n.eff","mcmcse::ess","coda::effectiveSize","posterior::ess_basic"), labels=c('stableGR: Slug-sail','mcmcse: Batch means','coda: AR','posterior: Geyer'))+
  facet_grid(cols=vars(S=S))
````


`posterior: Geyer` is on average clearly closer to 1 than the other
methods. `coda: AR` method is overconfident with short chains, but
has good behavior with longer chains. `stableGR: Slug-sail` has
quite unpredictable behavior being either over- or underconfident,
except in case of very long chains when the method is consistently
overconfident for antithetic chains and underconfident for
"thetic" chains. Not shown in the plot, but slug-sail estimator
had overall much higher variance than Geyer's and AR approaches.

Although the differences between methods are clear, the effect of
using the methods with bigger errors is likely to be small in most
actual Bayesian modeling use cases. Except for the shortest chains
with the highest autocorrelations, the errors in MCSE are at
highest 20\%, which should provide sufficient information whether
more draws are needed. With more draws the accuracy of all methods
improve.

### Mean of x^2

In the above the chains were simulated from AR(1) process, so we would
expect that `coda: AR` method would have some advantage. Also the
chains have normal(0,1) marginal which makes the empirical means
also to behave nicely. As an alternative we test the methods also
with the same AR processes, but values are squared so that the
chains are non-linear transformation of the AR process and the
marginal is skewed. Squared variable is, for example, a natural part
of variance computation.
```
x1 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x2 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x3 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
x4 = arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))^2;
```

The chosen $\phi$ values correspond to now ESS/$S$ values $(0.8, 1.0,
1.0, 0.8, 0.6, 0.3, 0.1)$. The squaring breaks the antithetic
behavior, but for simplicity we show the results for all different
values of $\phi$.


````{r plot2, echo=FALSE, fig.dim=c(9,3)}
load('ess_ar2_df.Rdata')
ggplot(df, aes(x=phi, y=z, 
               group=method,
               color=method)) +
  geom_line(alpha=0.8, size=1) +
  geom_hline(yintercept = 1, linetype='dashed') +
  coord_cartesian(ylim=c(0.91,1.4), clip='off')+
  labs(x='True ESS/S', y=TeX('RMS of $|\\mu -\\hat{\\mu}| / \\widehat{MCSE}$'))+
  guides(linetype = guide_legend(title = "N"),
         color = guide_legend(title = "Method"))+
  scale_x_continuous(breaks=phis, labels = round(tess/40000,1))+
  scale_color_bright(breaks=c("stableGR::n.eff","mcmcse::ess","coda::effectiveSize","posterior::ess_basic"), labels=c('stableGR: Slug-sail','mcmcse: Batch means','coda: AR','posterior: Geyer'))+
  facet_grid(cols=vars(S=S))
````


Again `posterior: Geyer` is on average clearly closer to 1 than the
other methods. All methods have bigger errors for the short chains
(S=4 x 100), especially when ESS/$S$ is small, which is natural as
the draws are from a skewed distribution and the variability in
means and correlations increases. With increasing number of draws
the error decreases for all methods.

### Probability p(x<0)

Next we examine the behavior for estimating probabilities. The
sequence is now binary with values 0 and 1, computed with an
indicator function I(x<0).
```
x1 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x2 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x3 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
x4 = as.double(arima.sim(n = N, list(ar = c(phi)), sd = sqrt((1-phi^2)))<0);
```

The chosen $\phi$ values correspond to now ESS/$S$ values $(1.4,
1.1, 0.9, 0.6, 0.4, 0.2, 0.1)$. We see super-efficiency for
antithetic chains.


````{r plot3, echo=FALSE, fig.dim=c(9,3)}
load('ess_arp_df.Rdata')
ggplot(df, aes(x=phi, y=z, 
               group=method,
               color=method)) +
  geom_line(alpha=0.8, size=1) +
  geom_hline(yintercept = 1, linetype='dashed') +
  coord_cartesian(ylim=c(0.91,1.4), clip='off')+
  labs(x='True ESS/S', y=TeX('RMS of $|\\mu -\\hat{\\mu}| / \\widehat{MCSE}$'))+
  guides(linetype = guide_legend(title = "N"),
         color = guide_legend(title = "Method"))+
  scale_x_continuous(breaks=phis, labels = round(tess/40000,1))+
  scale_color_bright(breaks=c("stableGR::n.eff","mcmcse::ess","coda::effectiveSize","posterior::ess_basic"), labels=c('stableGR: Slug-sail','mcmcse: Batch means','coda: AR','posterior: Geyer'))+
  facet_grid(cols=vars(S=S))
````


Again `posterior: Geyer` is on average clearly closer to 1 than the
other methods. All methods have bigger errors for the short chains
(S=4 x 100), especially when ESS/$S$ is small, which is natural as
binary observation contain less information than continuous
observations.  With increasing number of draws the error decreases
for all methods.

### Median of x

Quantiles are not expectations, but can be easily estimated from
MCMC draws. Computing MCSE requires additional steps. `stableGR`
and `coda` packages don't have a function for computing MCSE for
quantiles (or at least it is not mentioned in the
documentation). `mcmcse` package function `mcse.q` uses batch means
approach. `posterior` package function `mcse_quantile` uses the
inversion approach presented by Vehtari et al. (2021).


````{r plot4, echo=FALSE, fig.dim=c(9,3)}
load('ess_arq_df.Rdata')
clr<-colour("bright",names=FALSE)(7)
ggplot(df, aes(x=phi, y=z, 
               group=method,
               color=method)) +
  geom_line(alpha=0.8, size=1) +
  geom_hline(yintercept = 1, linetype='dashed') +
  coord_cartesian(ylim=c(0.95,1.25), clip='off')+
  labs(x='True ESS/S', y=TeX('RMS of $|\\mu -\\hat{\\mu}| / \\widehat{MCSE}$'))+
  guides(linetype = guide_legend(title = "N"),
         color = guide_legend(title = "Method"))+
  scale_x_continuous(breaks=phis, labels = round(tess/40000,1))+
  scale_color_manual(breaks=c("mcmcse::mcse.q","posterior::mcse_quantile"), labels=c('mcmcse: Batch means','posterior: Geyer + inv.prob.'), values=c(clr[2],clr[3]))+
  facet_grid(cols=vars(S=S))
````


The plots for `posterior: Geyer` and `mcmcse: batch means` look
similar as in the probability estimation which is expected due to
the close connection between computing cumulative probability and
quantile value.  `posterior: Geyer` line is on average closer to 1.

## Comparison of ESS estimators for bimodal distribution

Above, AR process was used to simulate MCMC sampling from a
unimodal distribution. We advocate running many chains not just for
the parallelization of the computation, but also to be able to
detect possible multimodality. Here we sample from a bimodal
distribution using Stan. We vary the number of chains and examine
the behavior of the ESS estimators in the same three packages.

`posterior` package is the only one of these packages taking into
account the the possibility that the chains are not mixing by using
also multi-chain \widehat{R} in ESS and MCSE
computations. `stableGR` and `coda` accept multiple chains as
input, but don't show in ESS estimates indication of between chain
mixing problems. `mcmcse` accepts only one chain as input, and
multiple chains were simply concatenated to provide a "single"
chain as input.

The model is a simple Student's $t_4$ distribution with unknown
location and scale.
```
data {int<lower=0> N; vector[N] y }
parameters {real mu;}
model {mu ~ student_t(4, 0, 100); y ~ student_t(4, mu, 1);}
```
The data is generated from a bimodal distribution.
```
N=20; y=c(rnorm(N/2, mean=-5, sd=1),rnorm(N/2, mean=5, sd=1));
```

With this data, the posterior is bimodal with well separated
modes. The modes don't necessarily have equal posterior
mass. Stan's dynamic HMC is not able to jump from one mode to
another. The random initialization determines to which mode each
chain ends up, and it is not possible to infer the actual relative
posterior masses from the chains. The number of chains in each mode
is random, and the probability of a chain with random
initialization ending to a mode depends on the volume of the
attraction area of that mode.  In such case we would like to get a
warning that the chains are not mixing.

The following plot shows an example of trace plot when one chain
is stuck in one mode and three in another mode.

````{r echo=FALSE, fig.dim=c(9,3)}
load('ess_df2.Rdata')
mcmc_trace(draws)
````


If we would repeat the sampling with random initializations and four
chains, we would observe 0--4 chains stuck in one mode and the rest
in the other mode. So there is still a possibility that all the
chains are stuck in one mode and we think that the posterior is
unimodal. With just one chain, we have probability of 0 recognizing
that there are well separated modes. With more chains, it is
possible that our random initialization is within the attraction
area of just one mode, and then having more chains doesn't help. In
general, with increasing number of chains, we have higher
probability of seeing more than one mode.

How should ESS estimates look like when we have chains that are not
mixing? If the modes are well separated so that between-chain
variance is much bigger than within-chain variances, each chain is
mostly indicating the loaction of the mode and not worth much more
than one observation.  The `posterior` package combines Geyer
truncated autocorrelation estimates with multi-chain convergence
diagnostic $\widehat{R}$. If the chains are not mixing, then the
draws within each chain are considered to be more correlated within
the chain and the multi-chain ESS estimate gets smaller. If the
modes are well separated, multi-chain ESS is close to the number of
chains. Arguably even this is an overestimate as increasing the
number of non-mixing chains does not provide reliable estimate of
the relative masses of the masses.

The following plot shows ESS per chain estimates using the four
packages and with increasing number of chains. Simulations have
been repeated 100 times.


````{r echo=FALSE, fig.dim=c(9,4)}
load('ess_df2.Rdata')
ggplot(df2, aes(x=log2(chains),
                y=ess/chains, color=factor(method))) +
  geom_jitter(width=0.07,height=0,alpha=1,shape=1) +
  geom_hline(yintercept = 1, linetype='dashed') +
  labs(x='Number of chains', y='Estimated ESS per chain')+
  guides(color = "none")+
  scale_x_continuous(breaks=0:4, labels = c(1,2,4,8,16))+
  scale_y_continuous(trans='log10')+
  scale_color_bright(breaks=c("1","2","3","4"), labels=c('stableGR','mcmcse','coda','posterior'))+
  facet_grid(cols=vars(methodlab))
````


With one chain, all packages consider only the within-chain
correlation and report similar ESS per chain values (~350). When
different chains end up to stuck in different well-separated modes,
we would prefer to get an estimate that is indicating poor
efficiency. With increasing number of chains, `coda` keeps
reporting similar ESS per chain (with less variation) and provides
no indication of non-mixing chains.  When at least on chain is
stuck in a different mode, `stableGR` reports ESS per chain of
approximately 60, which is much less than 350, but we could see
similar low values due to high autocorrelation and the total ESS is
high enough not to indicate that chains are not mixing
well. `mcmcse` does not have support for multiple chains, but
combining the chains to one chain, changes the autocorrelation
estimate so that when the number of chains increases, eventually
ESS per chain decreases close to 1, indicating inefficient
sampling.  `posterior` reports ESS per chain close to 1 always when
at least one chain is in the other mode, which is a clear
indication that something is wrong in the mixing of the chains.

## References

- Geyer, C. J. (1992). Practical Markov chain Monte Carlo. *Statistical Science*, 7:473–483.
- Gong, L., and Flegal, J. M. (2015). A practical sequential stopping rule for high-dimensional Markov chain Monte Carlo. *Journal of Computational and Graphical Statistics*, 25:684—700.
- Heidelberger, P., and Welch, P. D. (1981). A spectral method for confidence interval generation and run length control in simulations. *Communications of the ACM*, 24:233—245.
- Vats, D., and Knudson, C. (2018). Revisiting the Gelman-Rubin diagnostic. *arXiv preprint*, arXiv:1812.09384.
- Vats, D., and Knudson, C. (2021). Revisiting the Gelman-Rubin diagnostic. *Statistical Science*, 36(4): 518—529.
- Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., Bürkner, P.-C. (2021): Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC. *Bayesian analysis*, 16(2):667—718. [doi:10.1214/20-BA1221](https://doi.org/10.1214/20-BA1221).

