14 citations · 14 across the 7 of their papers we have counts for
7 papers
Using Transcripts for Nonparametric Monitoring of Serial Dependence
Christian H. Weiß, José M. Amigó
Control charts for process monitoring are widely used in practice. Most control charts require the monitored (residuals) process to be serially independent (and to satisfy specifie…
INARMA Models for Count Random Fields -- a Survey
Angelika Silbernagel, Christian H. Weiß
The thinning-based integer-valued autoregressive moving-average (INARMA) models are popular for count time series. Recently, types of INARMA models have also been developed for cou…
Novel Stein-type Characterizations of Bivariate Count Distributions with Applications
Shaochen Wang, Christian H. Weiß
The derivation and application of Stein identities have received considerable research interest in recent years, especially for continuous or discrete-univariate distributions. In…
Control Charts for Poisson Counts based on the Stein-Chen Identity
Christian H. Weiß
If monitoring Poisson count data for a possible mean shift (while the Poisson distribution is preserved), then the ordinary Poisson exponentially weighted moving-average (EWMA) con…
Fuzzy clustering of ordinal time series based on two novel distances with economic applications
Ángel López Oriona, Christian Weiss, José Antonio Vilar
Time series clustering is a central machine learning task with applications in many fields. While the majority of the methods focus on real-valued time series, very few works consi…
Conditional-mean Multiplicative Operator Models for Count Time Series
Christian H. Weiß, Fukang Zhu
Multiplicative error models (MEMs) are commonly used for real-valued time series, but they cannot be applied to discrete-valued count time series as the involved multiplication wou…
Penalized estimation of flexible hidden Markov models for time series of counts
Timo Adam, Roland Langrock, Christian H. Weiß
Hidden Markov models are versatile tools for modeling sequential observations, where it is assumed that a hidden state process selects which of finitely many distributions generate…