Results 11 to 20 of about 2,044,246 (250)

Forecasting emergency department arrivals using INGARCH models

Health Economics Review, 2023
Background Forecasting patient arrivals to hospital emergency departments is critical to dealing with surges and to efficient planning, management and functioning of hospital emerency departments.
Juan C. Reboredo, Jose Ramon Barba-Queiruga, Javier Ojea-Ferreiro, Francisco Reyes-Santias   +3 more
doaj   +1 more source

Autoregressive Models with Time-Dependent Coefficients—A Comparison between Several Approaches

Stats, 2022
Autoregressive-moving average (ARMA) models with time-dependent (td) coefficients and marginally heteroscedastic innovations provide a natural alternative to stationary ARMA models. Several theories have been developed in the last 25 years for parametric
Rajae Azrak, Guy Mélard
doaj   +1 more source

Monitoring Parameter Change for Time Series Models of Counts Based on Minimum Density Power Divergence Estimator

Entropy, 2020
In this study, we consider an online monitoring procedure to detect a parameter change for integer-valued generalized autoregressive heteroscedastic (INGARCH) models whose conditional density of present observations over past information follows one ...
Sangyeol Lee, Dongwon Kim
doaj   +1 more source

Observations on Sire Evaluation with Categorical Data Using Heteroscedastic Mixed Linear Models

Journal of Dairy Science, 1985
The ability of three mixed linear models to rank sires correctly for dichotomous and ordered tetrachotomous traits was studied using simulated half-sib progeny data. The models differed in the assumptions made regarding homogeneity of residual variance. Ranking ability was assessed by estimating the realized response to truncation selection (20% of the
A, Meijering, D, Gianola
openaire   +2 more sources

Bayesian Exploration of Phenomenological EoS of Neutron/Hybrid Stars with Recent Observations

Particles, 2023
The description of the stellar interior of compact stars remains as a big challenge for the nuclear astrophysics community. The consolidated knowledge is restricted to density regions around the saturation of hadronic matter ρ0=2.8×1014gcm−3, regimes ...
Emanuel V. Chimanski, Ronaldo V. Lobato, Andre R. Goncalves, Carlos A. Bertulani   +3 more
doaj   +1 more source

Effects of outliers on the identification and estimation of GARCH models [PDF]

, 2006
This paper analyses how outliers affect the identification of conditional heteroscedasticity and the estimation of generalized autoregressive conditionally heteroscedastic (GARCH) models.
Ruiz Ortega, Esther, Esther Ruiz, M. Angeles Carnero, Daniel Peña, Peña, Daniel, Carnero, María Ángeles, Ruiz, Esther   +6 more
core   +1 more source

Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning

International Journal of Applied Earth Observations and Geoinformation, 2022
The monitoring of soil moisture content (SMC) at very high spatial resolution (
Veronika Döpper, Alby Duarte Rocha, Katja Berger, Tobias Gränzig, Jochem Verrelst, Birgit Kleinschmit, Michael Förster   +6 more
doaj   +1 more source

Regression calibration for Cox regression under heteroscedastic measurement error - Determining risk factors of cardiovascular diseases from error-prone nutritional replication data [PDF]

, 2003
For instance nutritional data are often subject to severe measurement error, and an adequate adjustment of the estimators is indispensable to avoid deceptive conclusions.
Augustin, Thomas, Rummel, D., Döring, A.   +2 more
core   +1 more source

Efficient quantile regression for heteroscedastic models [PDF]

, 2015
Quantile regression (QR) provides estimates of a range of conditional quantiles. This stands in contrast to traditional regression techniques, which focus on a single conditional mean function. Lee et al.
MacEachern, Steve N,, Lee, Yoonkyung, Jung, Yoonsuh, Steven N. Maceachern, MacEachern, Steven N., Yoonsuh Jung, Yoonkyung Lee, Yoonsuh Jung (111157), Yoonkyung Lee (643212), Steven N. MacEachern (638105)   +9 more
core   +1 more source

Analysis of heteroscedasticity and correlation of repeated observations in Stated Preference(SP) data

KSCE Journal of Civil Engineering, 2002
The repeated measurement problems on Stated Preference (SP) data can be defined as the treatment of the combination of different variances (heteroscedasticity) and correlation of repeated observations from each individual. However, the repeated measurement problem has been approachedonly either as upward biased t-ratioor as correlation of disturbances ...
Hye-Jin Cho, Kang-Soo Kim
openaire   +1 more source