Results 171 to 180 of about 66,114 (285)

Learning in the Limit: Income Inference from Credit Extensions

The Journal of Finance, EarlyView.
ABSTRACT Combining a randomized controlled trial with administrative and survey data, this paper shows that credit limit extensions significantly increase total spending and income expectations. By controlling for changes in personal income expectations, the spending response to credit limit extensions weakens by approximately 30%.
XIAO YIN
wiley   +1 more source

Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models. [PDF]

Sensors (Basel)
Puder A, Zink M, Seidel L, Sax E.
europepmc   +1 more source

Comparison of Kalman Filters for Inertial Integrated Navigation. [PDF]

Sensors (Basel), 2019
Zhang M, Li K, Hu B, Meng C.
europepmc   +1 more source

Robust CDF‐Filtering of a Location Parameter

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania, Andrew C. Harvey, Alessandra Luati   +2 more
wiley   +1 more source

Bayesian model selection for COVID-19 pandemic state estimation using extended Kalman filters: Case study for Saudi Arabia. [PDF]

PLOS Glob Public Health
Alyami L, Das S, Townley S.
europepmc   +1 more source

Band‐Pass Filtering With High‐Dimensional Time Series. A Synthetic Indicator of the Medium‐to‐Long Run Component of Growth

Journal of Time Series Analysis, EarlyView.
ABSTRACT The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium‐to‐long‐run component of economic growth of a ...
Alessandro Giovannelli, Marco Lippi, Tommaso Proietti   +2 more
wiley   +1 more source

Fusion of High-Dynamic and Low-Drift Sensors Using Kalman Filters. [PDF]

Sensors (Basel), 2019
Wu B, Huang T, Jin Y, Pan J, Song K.
europepmc   +1 more source

Cointegration in a MIDAS Regression

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT Mixed data sampling (MIDAS) cointegration models are used to analyse variables observed at different frequencies. In this paper, we start from an assumed autoregressive distributed lag (ADL) model for high‐frequency observations, and derive the resulting representation when the dependent variable is only observed at a lower frequency.
H. Peter Boswijk, Philip Hans Franses
wiley   +1 more source

Digital twin with augmented state extended Kalman filters for forecasting electric power consumption of industrial production systems. [PDF]

Heliyon
Baldassarre A, Dion JL, Peyret N, Renaud F.   +3 more
europepmc   +1 more source

A Study about Kalman Filters Applied to Embedded Sensors. [PDF]

Sensors (Basel), 2017
Valade A, Acco P, Grabolosa P, Fourniols JY.   +3 more
europepmc   +1 more source