All Stories

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