INAR-hidden Markov chains to deal with misreported count data Since McKenzie presented the classical non-negative integer-valued autoregressive (INAR) model, the analysis of count time series has been rapidly growing in the past years, and many authors have been actively contributing to its improvement. However, many issues remain to be addressed in this field. In the […]
Effect of estimation under non-normality on the phase II performance of linear profile monitoring approaches Recently, there have been several studies about control charts to monitor profiles, where the quality of a process/product is expressed as function of response and explanatory variable(s). Mostly, it is assumed that the in-control parameter values are known and the […]
Ordinal Patterns and Ordinal Pattern Dependence Ordinal patterns describe the order structure of data points over a small time horizon. Using a moving window approach we reduce the complexity of a time series by analyzing the sequence of ordinal patterns instead of the original data. We present limit theorems for ordinal pattern probabilities and tests […]
Extrapolation of GIDAS accident data to Germany and Europe We investigate traffic accident data from project GIDAS (German In-Depth Accident Study). This project collects detailed accident data in two reference regions within Germany, Hanover and Dresden. For each accident with severely injured persons in these regions, the regular accident recording by police and medical staff […]
Testing discrete-valued time series for whiteness We consider the problem of testing a univariate discrete-valued time series for whiteness in the sequency domain, using Walsh–Fourier analysis. We show that the distribution of the lag window estimator of the Walsh spectral density is a scaled chi-square distribution, where the scale and degrees of freedom, both depend […]
Vine copula based post-processing of ensemble forecasts for temperature To account for forecast uncertainty in numerical weather prediction (NWP) models it has become common practice to employ ensemble prediction systems generating probabilistic forecast ensembles by multiple runs of the NWP model, each time with variations in the details of the numerical model and/or initial and […]
An axiomatic foundation of conditional logit This paper considers a decision maker choosing from a set of options when options have multiple real-valued attributes. Assuming DM chooses all options with positive probability, four invariance assumptions are necessary and sufficient for choice probabilities to take McFadden’s conditional logit form: independence of irrelevant alternatives, translation invariance, presentation […]
Soft-clipping INGARCH Models for Time Series of Bounded Counts The soft-clipping binomial INGARCH (scBINGARCH) models are proposed as nearly linear time series models for bounded counts with possibly negative autocorrelations. Conditions that guarantee the existence and certain mixing properties of the scBINGARCH process are derived, and further stochastic properties are discussed. The consistency and asymptotic […]
Clustering of categorical time series based on two novel feature-based distances with an application to biological sequences Two novel distances between categorical time series are introduced. Both of them measure discrepancy between extracted features describing the underlying serial dependence patterns. One of them is based on well-known association measures. The other relies on the so-called […]
Under weak moment conditions, we provide a functional central limit theorem (FCLT) for weighted sums of locally stationary processes for two main frameworks which differ in terms of the boundedness of the used function. Since the FCLT itself insinuates beneficial effects of a bootstrap analogue, we transfer our previous results to the bootstrap world using […]