Statistical inference for a general class of distributions with time-varying parameters
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Publication:5861419
DOI10.1080/02664763.2020.1763271OpenAlexW3026012715MaRDI QIDQ5861419
Alex Karagrigoriou, Vlad Stefan Barbu, Andreas Makrides
Publication date: 1 March 2022
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2020.1763271
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- Alternative approaches to study lifetime data under different scenarios: from the PH to the modified semiparametric AFT model
- An improved Akaike information criterion for state-space model selection
- hsmm -- an R package for analyzing hidden semi-Markov models
- Stylized facts of financial time series and hidden semi-Markov models
- Estimating the dimension of a model
- Semi-Markov modelling for multi-state systems
- Theory of statistics
- Likelihood testing with censored and missing duration data
- A Multiple Comparison Procedure Based on a Variant of the Schwarz Information Criterion in a Mixed Model
- Bayesian modelling of the mean and covariance matrix in normal nonlinear models
- Regression and time series model selection in small samples
- The asymptotic properties of ML estimators when sampling from associated populations
- Small Sample Robust Testing for Normality against Pareto Tails
- A Method for Multivariate Probability Distributions Construction via Parameter Dependence
- On entropy-based goodness-of-fit test for asymmetric Student-t and exponential power distributions
- On first-order integer-valued autoregressive process with Katz family innovations
- Robust estimation for non-homogeneous data and the selection of the optimal tuning parameter: the density power divergence approach
- The uniform distribution product: an approach to the (Q,r) inventory model using R
- On Small Samples Testing for Frailty Through Homogeneity Test
- On a type of dependency between Weibull lifetimes of system components
- A regression model selection criterion based on bootstrap bumping for use with resistant fitting.
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