Results 131 to 140 of about 2,471 (259)

Asymptotic properties of cross‐classified sampling designs

Canadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

"Within-Trial" Prognostic Score Adjustment Is Targeted Maximum Likelihood Estimation. [PDF]

Pharm Stat
Højbjerre-Frandsen E, Schuler A.
europepmc   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Post-selection inference for causal effects after causal discovery. [PDF]

Biometrika
Chang TH, Guo Z, Malinsky D.
europepmc   +1 more source

Jackknife bias‐corrected variance estimation for the generalized regression estimator

Canadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source

Aggregating dependent signals with heavy-tailed combination tests. [PDF]

Biometrika
Gui L, Jiang Y, Wang J.
europepmc   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Conscious simultaneity with continuous motion: a measure-theoretic resolution of the hard problem. [PDF]

Front Hum Neurosci
Sanfey J.
europepmc   +1 more source

The Benjamin–Ono Equation in the Zero‐Dispersion Limit for Rational Initial Data: Generation of Dispersive Shock Waves

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone, Louise Gassot, Patrick Gérard, Peter D. Miller   +3 more
wiley   +1 more source