Category: Regression with time series structure

Electricity price forecasting
Electricity price forecasting (EPF) is a branch of energy forecasting which focuses on predicting the spot and forward prices in wholesale electricity markets. Over the last 15 years electricity price
Sinusoidal model
In statistics, signal processing, and time series analysis, a sinusoidal model is used to approximate a sequence Yi to a sine function: where C is constant defining a mean level, α is an amplitude for
Generalized least squares
In statistics, generalized least squares (GLS) is a technique for estimating the unknown parameters in a linear regression model when there is a certain degree of correlation between the residuals in
Linear trend estimation
Linear trend estimation is a statistical technique to aid interpretation of data. When a series of measurements of a process are treated as, for example, a sequences or time series, trend estimation c
Political forecasting
Political forecasting aims at forecasting the outcomes of political events. Political events can be a number of events such as diplomatic decisions, actions by political leaders and other areas relati
Hildreth–Lu estimation
Hildreth–Lu estimation, named for Clifford Hildreth and , is a method for adjusting a linear model in response to the presence of serial correlation in the error term. It is an iterative procedure rel
First-hitting-time model
Events are often triggered when a stochastic or random process first encounters a threshold. The threshold can be a barrier, boundary or specified state of a system. The amount of time required for a
Newey–West estimator
A Newey–West estimator is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model where the standard assumptions of regression
Prais–Winsten estimation
In econometrics, Prais–Winsten estimation is a procedure meant to take care of the serial correlation of type AR(1) in a linear model. Conceived by Sigbert Prais and in 1954, it is a modification of C
Arellano–Bond estimator
In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator used to estimate dynamic models of panel data. It was proposed in 1991 by Manuel Arellano and Stephen Bond, ba
Heteroskedasticity-consistent standard errors
The topic of heteroskedasticity-consistent (HC) standard errors arises in statistics and econometrics in the context of linear regression and time series analysis. These are also known as heteroskedas
Unit root
In probability theory and statistics, a unit root is a feature of some stochastic processes (such as random walks) that can cause problems in statistical inference involving time series models. A line
Time-series regression
No description available.
Trend analysis
Trend analysis is the widespread practice of collecting information and attempting to spot a pattern. In some fields of study, the term has more formally defined meanings. Although trend analysis is o
Galton's problem
Galton's problem, named after Sir Francis Galton, is the problem of drawing inferences from cross-cultural data, due to the statistical phenomenon now called autocorrelation. The problem is now recogn
Cochrane–Orcutt estimation
Cochrane–Orcutt estimation is a procedure in econometrics, which adjusts a linear model for serial correlation in the error term. Developed in the 1940s, it is named after statisticians Donald Cochran
Breusch–Godfrey test
In statistics, the Breusch–Godfrey test is used to assess the validity of some of the modelling assumptions inherent in applying regression-like models to observed data series. In particular, it tests