Zobrazeno 1 - 10
of 160
pro vyhledávání: '"SHAH, RAJEN"'
Autor:
Young, Elliot H., Shah, Rajen D.
Generalized linear models are a popular tool in applied statistics, with their maximum likelihood estimators enjoying asymptotic Gaussianity and efficiency. As all models are wrong, it is desirable to understand these estimators' behaviours under mod
Externí odkaz:
http://arxiv.org/abs/2412.06119
Autor:
Young, Elliot H., Shah, Rajen D.
It is widely recognised that semiparametric efficient estimation can be hard to achieve in practice: estimators that are in theory efficient may require unattainable levels of accuracy for the estimation of complex nuisance functions. As a consequenc
Externí odkaz:
http://arxiv.org/abs/2410.03471
Autor:
Klyne, Harvey, Shah, Rajen D.
Single-parameter summaries of variable effects are desirable for ease of interpretation, but linear models, which would deliver these, may fit poorly to the data. A modern approach is to estimate the average partial effect -- the average slope of the
Externí odkaz:
http://arxiv.org/abs/2308.09207
Autor:
Young, Elliot H., Shah, Rajen D.
We study partially linear models in settings where observations are arranged in independent groups but may exhibit within-group dependence. Existing approaches estimate linear model parameters through weighted least squares, with optimal weights (giv
Externí odkaz:
http://arxiv.org/abs/2307.11401
Autor:
Guo, F. Richard, Shah, Rajen D.
Many testing problems are readily amenable to randomised tests such as those employing data splitting. However despite their usefulness in principle, randomised tests have obvious drawbacks. Firstly, two analyses of the same dataset may lead to diffe
Externí odkaz:
http://arxiv.org/abs/2301.02739
Testing the significance of a variable or group of variables $X$ for predicting a response $Y$, given additional covariates $Z$, is a ubiquitous task in statistics. A simple but common approach is to specify a linear model, and then test whether the
Externí odkaz:
http://arxiv.org/abs/2211.02039
Autor:
Pein, Florian, Shah, Rajen D.
Cross-validation is the standard approach for tuning parameter selection in many non-parametric regression problems. However its use is less common in change-point regression, perhaps as its prediction error-based criterion may appear to permit small
Externí odkaz:
http://arxiv.org/abs/2112.03220
Autor:
Stokell, Benjamin G., Shah, Rajen D.
There are a variety of settings where vague prior information may be available on the importance of predictors in high-dimensional regression settings. Examples include ordering on the variables offered by their empirical variances (which is typicall
Externí odkaz:
http://arxiv.org/abs/2109.11281
Knowing the causal structure of a system is of fundamental interest in many areas of science and can aid the design of prediction algorithms that work well under manipulations to the system. The causal structure becomes identifiable from the observat
Externí odkaz:
http://arxiv.org/abs/2108.08871
We study the problem of testing the null hypothesis that X and Y are conditionally independent given Z, where each of X, Y and Z may be functional random variables. This generalises testing the significance of X in a regression model of scalar respon
Externí odkaz:
http://arxiv.org/abs/2101.07108