1 |
Burnham KP and Anderson DR (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.), Springer-Verlag.
|
2 |
Garay AM, Lachos VH, Bolfarine H, and Cabral CRB (2017a). Linear censored regression models with scale mixtures of normal distributions, Statistical Papers, 58, 247-278.
DOI
|
3 |
Azzalini A and Dalla Valle A (1996). The multivariate skew-normal distribution, Biometrika, 83, 715-726.
DOI
|
4 |
Garay AW, Massuia MB, and Lachos VH (2017b). BayesCR: Bayesian Analysis of Censored Regression Models Under Scale Mixture of Skew Normal Distributions. R package version 2.1, http://cran.r-project.org/package=BayesCR
|
5 |
Lachos VH, Garay A, and Cabral CR (2020). Moments of truncated skew-normal/independent distributions, Brazilian Journal of Probability and Statistics, 34, 478-494.
|
6 |
Akaike H (1974). A new look at the statistical model identification, IEEE Transactions on Automatic Control, 19, 716-723.
DOI
|
7 |
Arellano-Valle RB, Castro LM, Gonzalez-Farias G and Munoz-Gajardo KA (2012). Student-t censored regression model: properties and inference, Statistical Methods & Applications, 21, 453-473.
DOI
|
8 |
Azzalini A (1985). A class of distributions which includes the normal ones, Scandinavian Journal of Statistics, 12, 171-178.
|
9 |
Azzalini A and Capitanio A (1999). Statistical applications of the multivariate skew normal distribution, Journal of the Royal Statistical Society: Series B, 61, 579-602.
DOI
|
10 |
Azzalini A and Capitanio A (2003). Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t-distribution, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 65, 367-389.
DOI
|
11 |
Basso RM, Lachos VH, Cabral CR, and Ghosh P (2010). Robust mixture modeling based on scale mixtures of skew-normal distributions, Computational Statistics & Data Analysis, 54, 2926-2941.
DOI
|
12 |
Bozdogan H (1987). Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions, Psychometrika, 52, 345-370.
DOI
|
13 |
Cronin V and Carver P (1998). Phonological sensitivity, rapid naming and beginning reading, Applied Psycholinguistics, 19, 447-461.
DOI
|
14 |
Dempster A, Laird N, and Rubin D (1977). Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B,, 39, 1-38.
|
15 |
Foulin JN (2005). Why is letter-name knowledge such a good predictor of learning to read?, Reading and Writting, 38, 129-155.
DOI
|
16 |
Galarza CM, Kan R, and Lachos VH (2020). MomTrunc: Moments of Folded and Doubly Truncated Multivariate Distributions, R package version 5.69, http://cran.r-project.org/package=MomTrunc
|
17 |
Liu C and Rubin DB (1994). The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence, Biometrika, 81, 633-648.
DOI
|
18 |
Louis TA (1982). Finding the observed information matrix when using the EM algorithm, Journal of the Royal Statistical Society: Series B (Methodological), 44, 226-233.
DOI
|
19 |
Massuia MB, Garay AM, Lachos VH and Cabral CRB (2017). Bayesian analysis of censored linear regression models with scale mixtures of skew-normal distributions, Statistics and its Interface, 10, 425-439,
DOI
|
20 |
Mattos TdB, Garay AM, and Lachos VH (2018). Likelihood-based inference for censored linear regression models with scale mixtures of skew-normal distributions, Journal of Applied Statistics, 45, 2039-2066.
DOI
|
21 |
Ritchey K and Speece D (2006). From letter names to word reading: The nascent role of sublexical fluency, Contemporary Educational Psychology, 31, 301-327.
DOI
|
22 |
Lachos VH, Moreno EJL, Chen K, and Cabral CRB (2017). Finite mixture modeling of censored data using the multivariate Student-t distribution, Journal of Multivariate Analysis, 159, 151-167.
DOI
|
23 |
Marston D and Magnusson D (1988). Alternative Educational Delivery Systems: Enhancing Instructional Options for All Students, (Ed. Graden J. and Zins, J. and Curtis, M.), Pages = 137-172, Publisher = National Association of School Psychology, Title = Curriculum-based measurement: District level implementation, Washington, DC.
|
24 |
Massuia MB, Cabral CRB, Matos LA and Lachos VH (2015). Influence diagnostics for Student-t censored linear regression models, Statistics, 49, 1074-1094.
DOI
|
25 |
RTI-FDA (2008). Snapshot of School Management Effectiveness: Peru Pilot Study (Technical report), USAID.
|
26 |
Schwarz G (1978). Estimating the dimension of a model, The Annals of Statistics, 6, 461-464.
DOI
|