Zobrazeno 1 - 10
of 446
pro vyhledávání: '"Shalizi, Cosma"'
Autor:
Farrell, Henry1 (AUTHOR) cshalizi@cmu.edu, Shalizi, Cosma2 (AUTHOR) henry.farrell@gmail.com
Publikováno v:
Communications of the ACM. Apr2024, Vol. 67 Issue 4, p25-28. 4p.
Dynamic stochastic general equilibrium (DSGE) models have been an ubiquitous, and controversial, part of macroeconomics for decades. In this paper, we approach DSGEs purely as statstical models. We do this by applying two common model validation chec
Externí odkaz:
http://arxiv.org/abs/2210.16224
Bayesian adaptive experimental design is a form of active learning, which chooses samples to maximize the information they give about uncertain parameters. Prior work has shown that other forms of active learning can suffer from active learning bias,
Externí odkaz:
http://arxiv.org/abs/2205.13698
Autor:
Shalizi, Cosma Rohilla
This brief pedagogical note re-proves a simple theorem on the convergence, in $L_2$ and in probability, of time averages of non-stationary time series to the mean of expectation values. The basic condition is that the sum of covariances grows sub-qua
Externí odkaz:
http://arxiv.org/abs/2203.09085
Autor:
Shalizi, Cosma Rohilla
Using Markov chain Monte Carlo to sample from posterior distributions was the key innovation which made Bayesian data analysis practical. Notoriously, however, MCMC is hard to tune, hard to diagnose, and hard to parallelize. This pedagogical note exp
Externí odkaz:
http://arxiv.org/abs/2203.09077
Autor:
Shalizi, Cosma Rohilla
We can, and should, do statistical inference on simulation models by adjusting the parameters in the simulation so that the values of {\em randomly chosen} functions of the simulation output match the values of those same functions calculated on the
Externí odkaz:
http://arxiv.org/abs/2111.09220
Fields like public health, public policy, and social science often want to quantify the degree of dependence between variables whose relationships take on unknown functional forms. Typically, in fact, researchers in these fields are attempting to eva
Externí odkaz:
http://arxiv.org/abs/1912.03387
Autor:
Lunde, Robert, Shalizi, Cosma Rohilla
We consider the problem of finding confidence intervals for the risk of forecasting the future of a stationary, ergodic stochastic process, using a model estimated from the past of the process. We show that a bootstrap procedure provides valid confid
Externí odkaz:
http://arxiv.org/abs/1711.02834
A very popular class of models for networks posits that each node is represented by a point in a continuous latent space, and that the probability of an edge between nodes is a decreasing function of the distance between them in this latent space. We
Externí odkaz:
http://arxiv.org/abs/1711.02123
Autor:
Green, Alden, Shalizi, Cosma Rohilla
Publikováno v:
Electronic Journal of Statistics, vol. 16 (2022), pp. 1058--1095
We introduce two new bootstraps for exchangeable random graphs. One, the "empirical graphon bootstrap", is based purely on resampling, while the other, the "histogram bootstrap", is a model-based "sieve" bootstrap. We show that both of them accuratel
Externí odkaz:
http://arxiv.org/abs/1711.00813