Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Christian H. Weiß"'
Autor:
Huiqiao Wang, Christian H. Weiß
Publikováno v:
Entropy, Vol 26, Iss 2, p 168 (2024)
The novel circumstance-driven bivariate integer-valued autoregressive (CuBINAR) model for non-stationary count time series is proposed. The non-stationarity of the bivariate count process is defined by a joint categorical sequence, which expresses th
Externí odkaz:
https://doaj.org/article/ad9a58685934437d8fc54d8e32563ae6
Autor:
Christian H. Weiß
Publikováno v:
Entropy, Vol 25, Iss 12, p 1576 (2023)
Time series are sequentially observed data in which important information about the phenomenon under consideration is contained not only in the individual observations themselves, but also in the way these observations follow one another [...]
Externí odkaz:
https://doaj.org/article/23de2cd6d8f04426ad1371e749a685b7
Publikováno v:
Entropy, Vol 25, Iss 1, p 105 (2023)
In a time series context, the study of the partial autocorrelation function (PACF) is helpful for model identification. Especially in the case of autoregressive (AR) models, it is widely used for order selection. During the last decades, the use of A
Externí odkaz:
https://doaj.org/article/1bf90b88b38a4452895de558a51a42a8
Autor:
Christian H. Weiß
Publikováno v:
Entropy, Vol 24, Iss 1, p 42 (2021)
The family of cumulative paired ϕ-entropies offers a wide variety of ordinal dispersion measures, covering many well-known dispersion measures as a special case. After a comprehensive analysis of this family of entropies, we consider the correspondi
Externí odkaz:
https://doaj.org/article/3838b7b10c5a4853a249aa1df052aeb9
Autor:
Christian H. Weiß
Publikováno v:
Entropy, Vol 23, Iss 9, p 1163 (2021)
Time series consist of data observed sequentially in time, and they are assumed to stem from an underlying stochastic process [...]
Externí odkaz:
https://doaj.org/article/e0bfb750f3264ba2b3f7c5c9b18fa3cb
Autor:
Christian H. Weiß
Publikováno v:
Entropy, Vol 22, Iss 4, p 458 (2020)
For the modeling of categorical time series, both nominal or ordinal time series, an extension of the basic discrete autoregressive moving-average (ARMA) models is proposed. It uses an observation-driven regime-switching mechanism, leading to the fam
Externí odkaz:
https://doaj.org/article/dd5873727a244085b4fe16528d078fd4
Publikováno v:
Econometrics, Vol 7, Iss 3, p 30 (2019)
In forecasting count processes, practitioners often ignore the discreteness of counts and compute forecasts based on Gaussian approximations instead. For both central and non-central point forecasts, and for various types of count processes, the perf
Externí odkaz:
https://doaj.org/article/20fe36b675ad4c4cb5c7dda9961d4c9c
Autor:
Christian H. Weiß
Publikováno v:
Econometrics, Vol 7, Iss 2, p 17 (2019)
The analysis and modeling of categorical time series requires quantifying the extent of dispersion and serial dependence. The dispersion of categorical data is commonly measured by Gini index or entropy, but also the recently proposed extropy measure
Externí odkaz:
https://doaj.org/article/f7cb70f5fbb34180a0de7eb9b022975d
Autor:
Christian H. Weiß
Dieses Werk stellt eine kompakte und zugleich umfassende Einführung zu Mathematica dar, einem sehr populären und äußerst vielseitigen Computeralgebrasystem, welches auf der Programmiersprache Wolfram Language beruht. Mathematica bietet ein breite
Autor:
Shaochen Wang, Christian H. Weiß
Publikováno v:
Mathematics and Computers in Simulation. 212:310-322