Tests for Changes in Count Time Series Models With Exogenous Covariates
ABSTRACT We deal with a parametric change in models for count time series with exogenous covariates specified via the conditional distribution, i.e., with integer generalized autoregressive conditional heteroscedastic models with covariates (INGARCH‐X).
Šárka Hudecová, Marie Hušková
wiley +1 more source
Research on the estimation method of crop net primary productivity based on improved CASA model. [PDF]
Li W +7 more
europepmc +1 more source
Time‐Varying Dispersion Integer‐Valued GARCH Models
ABSTRACT We introduce a general class of INteger‐valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing simultaneously time‐varying mean and dispersion parameters. We call such models time‐varying dispersion INGARCH (tv‐DINGARCH) models.
Wagner Barreto‐Souza +3 more
wiley +1 more source
Role of rivaroxaban in arteriovenous graft thrombosis after endovascular treatment and establishment and evaluation of a nomogram predictive model for postoperative recurrent thrombosis risk. [PDF]
Wang M +6 more
europepmc +1 more source
Extremely Fast Maximum Likelihood Estimation of High‐Order Autoregressive Models
ABSTRACT We consider the problem of exact maximum likelihood estimation of potentially high‐order (p>50$$ p>50 $$) autoregressive models. We propose an extremely fast coordinate‐wise algorithm for fitting autoregressive models. This fast algorithm exploits several properties of the negative log‐likelihood when parameterised in terms of partial ...
Daniel F. Schmidt, Enes Makalic
wiley +1 more source
A New Hybrid Adaptive Self-Loading Filter and GRU-Net for Active Noise Control in a Right-Angle Bending Pipe of an Air Conditioner. [PDF]
Zhu W +5 more
europepmc +1 more source
Online Detection of Forecast Model Inadequacies Using Forecast Errors
ABSTRACT In many organizations, accurate forecasts are essential for making informed decisions in a variety of applications, from inventory management to staffing optimization. Whatever forecasting model is used, changes in the underlying process can lead to inaccurate forecasts, which will be damaging to decision‐making.
Thomas Grundy +2 more
wiley +1 more source
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models. [PDF]
Ai L +3 more
europepmc +1 more source
Density‐Valued ARMA Models by Spline Mixtures
ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley +1 more source
Entropy-driven online open circuit voltage identification for precise state estimation in lithium-ion batteries. [PDF]
Li Z, Chen C, Yang R, Li H, Xiong R.
europepmc +1 more source

