All Stories

  1. Modeling Bounded Count Environmental Data Using a Contaminated Beta‐Binomial Regression Model
  2. Designing unsupervised mixed‐type feature selection techniques using the heterogeneous correlation matrix
  3. Heckman selection-contaminated normal model
  4. Handling skewness and directional tails in model-based clustering
  5. Discrete mode-mixtures of unimodal positive distributions with an application to solar energy in South Africa
  6. LRDP: an R package implementing a new class of decompositions for orthogonal matrices
  7. Finite mixtures of multivariate skew tail-inflated normal distributions
  8. An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data
  9. On the Number of Components for Matrix‐Variate Mixtures: A Comparison Among Information Criteria
  10. Hidden semi-Markov models for rainfall-related insurance claims
  11. A refreshing take on the inverted Dirichlet via a mode parameterization with some statistical illustrations
  12. Asymmetric Laplace scale mixtures for the distribution of cryptocurrency returns
  13. A New Look at the Dirichlet Distribution: Robustness, Clustering, and Both Together
  14. Mode mixture of unimodal distributions for insurance loss data
  15. Women and insurance pricing policies: a gender-based analysis with GAMLSS on two actuarial datasets
  16. The generalized hyperbolic family and automatic model selection through the multiple‐choiceLASSO
  17. Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions
  18. Parsimonious mixtures for the analysis of tensor-variate data
  19. Model-based clustering using a new multivariate skew distribution
  20. Matrix-Variate Hidden Markov Regression Models: Fixed and Random Covariates
  21. On stylized facts of cryptocurrencies returns and their relationship with other assets, with a focus on the impact of COVID-19
  22. Model-based clustering via skewed matrix-variate cluster-weighted models
  23. Parsimonious hidden Markov models for matrix-variate longitudinal data
  24. Dimension-wise scaled normal mixtures with application to finance and biometry
  25. Assessing Measurement Invariance for Longitudinal Data through Latent Markov Models
  26. Mixtures of Matrix-Variate Contaminated Normal Distributions
  27. Multiple scaled symmetric distributions in allometric studies
  28. Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies
  29. Two new matrix-variate distributions with application in model-based clustering
  30. Unconstrained representation of orthogonal matrices with application to common principal components
  31. The multivariate tail-inflated normal distribution and its application in finance
  32. Dichotomous unimodal compound models: application to the distribution of insurance losses
  33. Leptokurtic moment-parameterized elliptically contoured distributions with application to financial stock returns
  34. Robust model-based clustering with mild and gross outliers
  35. Multivariate hidden Markov regression models: random covariates and heavy-tailed distributions
  36. High-dimensional unsupervised classification via parsimonious contaminated mixtures
  37. A Random-covariate Approach for Distal Outcome Prediction with Latent Class Analysis
  38. Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition
  39. A new look at the inverse Gaussian distribution with applications to insurance and economic data
  40. Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population
  41. On the Use of the Sub-Gaussian $$\alpha $$α-Stable Distribution in the Cluster-Weighted Model
  42. Fitting insurance and economic data with outliers: a flexible approach based on finite mixtures of contaminated gamma distributions
  43. Mixtures of multivariate contaminated normal regression models
  44. Compound unimodal distributions for insurance losses
  45. Dealing with omitted answers in a survey on social integration of immigrants in Italy
  46. Testing for serial independence
  47. The multivariate leptokurtic-normal distribution and its application in model-based clustering
  48. A diagram to detect serial dependencies: an application to transport time series
  49. Clustering Multivariate Longitudinal Observations: The Contaminated Gaussian Hidden Markov Model
  50. Multilevel cluster-weighted models for the evaluation of hospitals
  51. Parsimonious mixtures of multivariate contaminated normal distributions
  52. Spatial attraction in migrants' settlement patterns in the city of Catania
  53. Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers
  54. Decision boundaries for mixtures of regressions
  55. The Kullback–Leibler autodependogram
  56. Hypothesis Testing for Mixture Model Selection
  57. A time-dependent extension of the projected normal regression model for longitudinal circular data based on a hidden Markov heterogeneity structure
  58. Clustering bivariate mixed-type data via the cluster-weighted model
  59. Erratum to: The Generalized Linear Mixed Cluster-Weighted Model
  60. The Generalized Linear Mixed Cluster-Weighted Model
  61. Cluster-weighted $$t$$ t -factor analyzers for robust model-based clustering and dimension reduction
  62. SDD : An R Package for Serial Dependence Diagrams
  63. Parsimonious Generalized Linear Gaussian Cluster-Weighted Models
  64. Bivariate discrete beta Kernel graduation of mortality data
  65. On the Upward Bias of the Dissimilarity Index and Its Corrections
  66. Flexible mixture modelling with the polynomial Gaussian cluster-weighted model
  67. Model-based clustering via linear cluster-weighted models
  68. Refusal to Answer Specific Questions in a Survey: A Case Study
  69. KernSmoothIRT : An R Package for Kernel Smoothing in Item Response Theory
  70. DBKGrad : An R Package for Mortality Rates Graduation by Discrete Beta Kernel Techniques
  71. Estimating a Rasch Model via Fuzzy Empirical Probability Functions
  72. On the Spectral Decomposition in Normal Discriminant Analysis
  73. Closed Likelihood Ratio Testing Procedures to Assess Similarity of Covariance Matrices
  74. Clustering and classification via cluster-weighted factor analyzers
  75. Testing Serial Independence via Density-Based Measures of Divergence
  76. Detecting serial dependencies with the reproducibility probability autodependogram
  77. Using the Autodependogram in Model Diagnostic Checking
  78. Using the Variation Coefficient for Adaptive Discrete Beta Kernel Graduation
  79. Finite mixtures of unimodal beta and gamma densities and the $$k$$ -bumps algorithm
  80. Graduation by Adaptive Discrete Beta Kernels
  81. Checking Serial Independence of Residuals from a Nonlinear Model
  82. The autodependogram: a graphical device to investigate serial dependences
  83. Discrete approximations of continuous and mixed measures on a compact interval
  84. Assessing the pattern of covariance matrices via an augmentation multiple testing procedure
  85. Discrete Beta Kernel Graduation of Age-Specific Demographic Indicators
  86. Discrete Beta-Type Models
  87. Considerations on the Impact of Ill-Conditioned Configurations in the CML Approach