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Combination of biased forecasts: Bias correction or bias based weights?

Wenzel, Thomas - 1999

Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts,...

Persistent link: https://www.econbiz.de/10010316655

Combination of biased forecasts : bias correction or bias based weights?

Wenzel, Thomas - 1999

Persistent link: https://www.econbiz.de/10009789914

Scalar mean square error optimal linear combination of multivariate forecasts

Troschke, Sven-Oliver - 2002

When a forecaster predicts the future value of a certain random variable it is very likely that he will not only forecast that certain variable but he will also forecast other variables from the same field. In the literature on the combination of several individual forecasts univariate...

Persistent link: https://www.econbiz.de/10009775960

Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned

Grün, Bettina; Kosmidis, Ioannis; Zeileis, Achim - 2011

Beta regression - an increasingly popular approach for modeling rates and proportions - is extended in various … directions: (a) bias correction/reduction of the maximum likelihood estimator, (b) beta regression tree models by means of … recursive partitioning, (c) latent class beta regression by means of finite mixture models. All three extensions may be of …

Persistent link: https://www.econbiz.de/10010294793

Panel regression with random noise

Ronning, Gerd; Schneeweiss, Hans - 2009

The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct consistent and asymptotically normal estimators. In addition, we...

Persistent link: https://www.econbiz.de/10010264605

Robust small area estimation under spatial non-stationarity

Baldermann, Claudia; Salvati, Nicola; Schmid, Timo - 2016

Geographically weighted small area methods have been studied in literature for small area estimation. Although these approaches are useful for the estimation of small area means efficiently under strict parametric assumptions, they can be very sensitive to outliers in the data. In this paper, we...

Persistent link: https://www.econbiz.de/10011455039