Results 51 to 60 of about 33,702 (146)
Estimating a convex function in nonparametric regression [PDF]
A new nonparametric estimate of a convex regression function is proposed and its stochastic properties are studied. The method starts with an unconstrained estimate of the derivative of the regression function, which is firstly isotonized and then ...
Birke, Melanie, Dette, Holger
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Nonparametric inference of doubly stochastic Poisson process data via the kernel method
, 2011 Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference ...
Kou, S. C., Zhang, Tingting
core +1 more source
Journal of Time Series Analysis, EarlyView.ABSTRACT We propose a new formulation of the Vašičekmodel within the framework of functional data analysis. We treat observations (continuous‐time rates) within a suitably defined trading day as a single statistical object. We then consider a sequence of such objects, indexed by day.
Piotr Kokoszka +4 more
wiley +1 more source
Density‐Valued ARMA Models by Spline Mixtures
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
Semiparametric Estimation in Time Series of Simultaneous Equations [PDF]
A system of vector semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components.
Jiti Gao, Peter C. B. Phillips
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Fully Modified GLS Estimation for Seemingly Unrelated Cointegrating Polynomial Regressions
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT A new feasible generalized least squares estimator is proposed. Our estimator incorporates (1) the inverse autocovariance matrix of multidimensional errors, and (2) second‐order bias corrections. The resulting estimator has the intuitive interpretation of applying a weighted least squares objective function to filtered data series.
Yicong Lin, Hanno Reuvers
wiley +1 more source
Scandinavian Journal of Psychology, EarlyView.ABSTRACT Identifying the drivers of chronic stress is crucial for understanding its impact on mental health. Latent toxoplasmosis, a widespread parasitic infection, has been linked to various psychological changes. The Stress‐Coping Hypothesis proposes that at least some of these changes are consequences of chronic stress arising from the infection's ...
Jaroslav Flegr +2 more
wiley +1 more source
Sensitivity analysis for generalized estimating equation with non‐ignorable missing data
Scandinavian Journal of Statistics, EarlyView.Abstract Many incomplete‐data statistical inference procedures are developed under the missing at random (MAR) assumption. However, the MAR assumption has been criticized as being overly strong for real‐data problems, and is unverifiable by using observed data. To handle data that are missing not at random (MNAR), sensitivity analysis has been proposed
Hui Gong, Kin Wai Chan
wiley +1 more source
Empirical Likelihood for Regression Discontinuity Design [PDF]
This paper proposes empirical likelihood based inference methods for causal effects identified from regression discontinuity designs. We consider both the sharp and fuzzy regression discontinuity designs and treat the regression functions as ...
Ke-Li Xu, Taisuke Otsu
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