Results 121 to 130 of about 33,661 (311)

Inflation convergence after the introduction of the Euro [PDF]

open access: yes
Using the Johansen test for cointegration, we examine to which extent inflation rates in the Euro area have converged after the introduction of a single currency.
Markus Mentz,, Steffen P. Sebastian
core  

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne   +2 more
wiley   +1 more source

Asymptotic properties of the Bernstein density copula for dependent data [PDF]

open access: yes
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based.
ROMBOUTS, Jeroen V.K.   +2 more
core  

Asymptotic properties of cross‐classified sampling designs

open access: yesCanadian 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

Bayesian inverse ensemble forecasting for COVID‐19

open access: yesCanadian 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

A goodness‐of‐fit test for regression models with discrete outcomes

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang   +2 more
wiley   +1 more source

Asymptotic null distributions of stationarity and nonstationarity [PDF]

open access: yes
The purpose of this paper is to investigate the asymptotic null distribution of stationarity and nonstationarity tests when the distribution of the error term belongs to the normal domain of attraction of a stable law in any finite sample but the error ...
Nunzio Cappuccio, Diego Lubian
core  

A partial envelope approach for modelling multivariate spatial‐temporal data

open access: yesCanadian 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   +3 more
wiley   +1 more source

Convergence of asymptotic systems with unbounded delays with applications to Cohen-Grossberg neural networks and Lotka-Volterra systems

open access: yes
This thesis studies the dynamics of two prominent classes of models: Cohen-Grossberg neural network (CGNN) and Lotka-Volterra ecological systems. Firstly, we investigate the global exponential stability and the existence of a periodic solution of a ...
Elmwafy, Ahmed Osama Mohamed Sayed Sayed
core  

Nonlinear permuted Granger causality

open access: yesCanadian 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

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