Results 181 to 190 of about 190,253 (294)
Multivariate mixed models accounting for don't know options in ordinal data. [PDF]
Gueorguieva R, Iannario M.
europepmc +1 more source
Mortality Forecasting Using Variational Inference
ABSTRACT This paper considers the problem of forecasting mortality rates. A large number of models have already been proposed for this task, but they generally have the disadvantage of either estimating the model in a two‐step process, possibly losing efficiency, or relying on methods that are cumbersome for the practitioner to use.
Patrik Andersson, Mathias Lindholm
wiley +1 more source
Measuring Statistical Dependence via Characteristic Function IPM. [PDF]
Daniušis P +3 more
europepmc +1 more source
A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley +1 more source
Hybrid kernels integrating genomic and multispectral data improve wheat genomic prediction accuracy. [PDF]
Montesinos-López OA +8 more
europepmc +1 more source
ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio +1 more
wiley +1 more source
Inference in group sequential designs with causal mechanisms: implications for power and mediation analysis. [PDF]
Lee KM, Emsley R.
europepmc +1 more source
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source
Predicting enviromically adapted varieties with big data. [PDF]
Gogna A +7 more
europepmc +1 more source
Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer +3 more
wiley +1 more source

