Forecasting using predictor selection from a large set of highly correlated variables
نویسندگان
چکیده
منابع مشابه
Bayesian forecasting with highly correlated predictors
This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.
متن کاملA family of large set of size nine
We investigate the existence of some large sets of size nine. The large set $LS[9](2,5,29)$ is constructed and existence of the family $LS[9](2,5,27l+j)$ for $lgeq 1, 2leq j
متن کاملForecasting Using Principal Components from a Large Number of Predictors
This article considers forecasting a single time series when there are many predictors (N) and time series observations (T). When the data follow an approximate factor model, the predictors can be summarized by a small number of indexes, which we estimate using principal components. Feasible forecasts are shown to be asymptotically efficient in the sense that the difference between the feasible...
متن کاملFeature Set Selection for On-Line Signatures Using Selection of Regression Variables
In this paper we approach feature set selection phase in signature verification by applying the method for selection of regression variables based on Mallows Cp criterion for regression. In this way we identify best feature subsets of various sizes for each user of our database on the basis of his/her ten genuine and ten random forgery on-line signatures. Among these subsets we select the best ...
متن کاملTactical sales forecasting using a very large set of macroeconomic indicators
Tactical forecasting in supply chain management supports planning for inventory, scheduling production, and raw material purchase, amongst other functions. It typically refers to forecasts up to 12 months ahead. Traditional forecasting models take into account univariate information extrapolating from the past, but cannot anticipate macroeconomic events, such as steep increases or declines in n...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Technology and Nanotechnology
سال: 2019
ISSN: 1613-0073
DOI: 10.18287/1613-0073-2019-2416-10-18