565 citations · 646 across the 14 of their papers we have counts for
15 papers
SARS-CoV-2 Transmission in University Classes
William Ruth, Richard Lockhart
We investigate transmission dynamics for SARS-CoV-2 on a real network of classes at Simon Fraser University, a medium-sized school in Western Canada. Outbreaks are simulated over t…
Cramer-von Mises tests for Change Points
Rasmus Erlemann, Richard Lockhart, Rihan Yao
We study two nonparametric tests of the hypothesis that a sequence of independent observations is identically distributed against the alternative that at a single change point the…
A Generalized Hosmer-Lemeshow Goodness-of-Fit Test for a Family of Generalized Linear Models
Nikola Surjanovic, Richard Lockhart, Thomas M. Loughin
Generalized linear models (GLMs) are used within a vast number of application domains. However, formal goodness of fit (GOF) tests for the overall fit of the modelso-called "glo…
Partial least squares for sparsely observed curves with measurement errors
Zhiyang Zhou, Richard A. Lockhart
Functional partial least squares (FPLS) is commonly used for fitting scalar-on-function regression models. For the sake of accuracy, FPLS demands that each realization of the funct…
A goodness of fit test for two component two parameter Weibull mixtures
Richard A. Lockhart, Chandanie W. Navaratna
Fitting mixture distributions is needed in applications where data belongs to inhomogeneous populations comprising homogeneous sub-populations. The mixing proportions of the sub po…
On comparison of estimators for proportional error nonlinear regression models in the limit of small measurement error
Richard A. Lockhart, Chandanie W. Navaratna
In this paper, we compare maximum likelihood (ML), quasi likelihood (QL) and weighted least squares (WLS) estimators for proportional error nonlinear regression models. Literature…
Bayes factors with (overly) informative priors
Richard A Lockhart
Priors in which a large number of parameters are specified to be independent are dangerous; they make it hard to learn from data. I present a couple of examples from the literature…
Comments on `High-dimensional simultaneous inference with the bootstrap'
Richard A. Lockhart, Richard J. Samworth
We provide some comments on the article `High-dimensional simultaneous inference with the bootstrap' by Ruben Dezeure, Peter Buhlmann and Cun-Hui Zhang.
Inefficient Best Invariant Tests
Richard A Lockhart
Test statistics which are invariant under various subgroups of the orthogonal group are shown to provide tests whose powers are asymptotically equal to their level against the usua…
A Bayesian Search for the Higgs Particle
Shirin Golchi, Richard Lockhart
The statistical procedure used in the search for the Higgs boson is investigated in this paper. A Bayesian hierarchical model is proposed that uses the information provided by the…
Rejoinder: "A significance test for the lasso"
Richard Lockhart, Jonathan Taylor, Ryan J. Tibshirani +1
Rejoinder of "A significance test for the lasso" by Richard Lockhart, Jonathan Taylor, Ryan J. Tibshirani, Robert Tibshirani [arXiv:1301.7161].
Exact Post-Selection Inference for Sequential Regression Procedures
Ryan J. Tibshirani, Jonathan Taylor, Richard Lockhart +1
We propose new inference tools for forward stepwise regression, least angle regression, and the lasso. Assuming a Gaussian model for the observation vector y, we first describe a g…
A significance test for the lasso
Richard Lockhart, Jonathan Taylor, Ryan J. Tibshirani +1
In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of models visited along…
Conditional limit laws for goodness-of-fit tests
Richard A. Lockhart
We study the conditional distribution of goodness of fit statistics of the Cramér--von Mises type given the complete sufficient statistics in testing for exponential family models.…
Methods to distinguish between polynomial and exponential tails
Joan del Castillo, Jalila Daoudi, Richard Lockhart
In this article two methods to distinguish between polynomial and exponential tails are introduced. The methods are mainly based on the properties of the residual coefficient of va…