In many time series models, an infinite number of moments can be used for estimation in a large sample. I supply a technically undemanding proof of a condition for optimal instrumental variables use ...
R code for the simulation of certain stationary Gaussian time series (e.g., fractionally differenced (FD) and fractional Gaussian noise (fGn) processes) using the Davies-Harte algorithm. The process ...
Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications
Combining ideas from statistics and time-series analysis, Wiener used Gauss's method of shaping the characteristic of a detector to allow for the maximal recognition of signals in the presence of ...
Time series regression models are useful for analyzing the relationship between a dependent variable and one or more independent variables that change over time. However, time series data often ...
yielding a strong method for non-stationary time-series forecasting. Experiments on real world datases in the long sequence time-series forecasting setting demonstrates that DeepTime achieves ...
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