Forecast combinations: An over 50-year review
Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …
recent years, have become part of mainstream forecasting research and activities …
Distributional regression for data analysis
N Klein - Annual Review of Statistics and Its Application, 2024 - annualreviews.org
Flexible modeling of how an entire distribution changes with covariates is an important yet
challenging generalization of mean-based regression that has seen growing interest over …
challenging generalization of mean-based regression that has seen growing interest over …
[HTML][HTML] Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin
We study whether news and sentiment about bitcoin regulation, the hacking of bitcoin
exchanges and scheduled macroeconomic news announcements affect the volatility of …
exchanges and scheduled macroeconomic news announcements affect the volatility of …
[图书][B] Regressionsmodelle
Alle im vorigen Kapitel beschriebenen Problemstellungen besitzen eine wesentliche
Gemeinsamkeit: Eigenschaften einer Zielvariablen y sollen in Abhängigkeit von Kovariablen …
Gemeinsamkeit: Eigenschaften einer Zielvariablen y sollen in Abhängigkeit von Kovariablen …
[图书][B] The Oxford handbook of panel data
BH Baltagi - 2015 - books.google.com
The Oxford Handbook of Panel Data examines new developments in the theory and
applications of panel data. It includes basic topics like non-stationary panels, co-integration …
applications of panel data. It includes basic topics like non-stationary panels, co-integration …
Quantile regression as a generic approach for estimating uncertainty of digital soil maps produced from machine-learning
B Kasraei, B Heung, DD Saurette, MG Schmidt… - … Modelling & Software, 2021 - Elsevier
Digital soil mapping (DSM) techniques have provided soil information that has
revolutionized soil management across multiple spatial extents and scales. DSM …
revolutionized soil management across multiple spatial extents and scales. DSM …
Rage against the mean–a review of distributional regression approaches
Distributional regression models that overcome the traditional focus on relating the
conditional mean of the response to explanatory variables and instead target either the …
conditional mean of the response to explanatory variables and instead target either the …
Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes
AJ Cannon - Stochastic environmental research and risk …, 2018 - Springer
The goal of quantile regression is to estimate conditional quantiles for specified values of
quantile probability using linear or nonlinear regression equations. These estimates are …
quantile probability using linear or nonlinear regression equations. These estimates are …
Beyond expectation: Deep joint mean and quantile regression for spatiotemporal problems
F Rodrigues, FC Pereira - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
Spatiotemporal problems are ubiquitous and of vital importance in many research fields.
Despite the potential already demonstrated by deep learning methods in modeling …
Despite the potential already demonstrated by deep learning methods in modeling …
A multi-step probability density prediction model based on gaussian approximation of quantiles for offshore wind power
W Zhang, Y He, S Yang - Renewable Energy, 2023 - Elsevier
With the increasing utilization of offshore wind power, accurate prediction of offshore wind
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …