All Stories

  1. Stochastic Processes with R: An Introduction
  2. Essentials of Econometrics
  3. Time Series for Data Sciences: Analysis and Forecasting
  4. Introduction to Statistics and Data Analysis (with Exercises, Solutions and Applications in R)
  5. Dynamic space–time panel data models: An eigendecomposition-based bias-corrected least squares procedure
  6. Estimation of Reliability in Multicomponent Set-up when Stress and Strength are Non-identical
  7. Robust dynamic space–time panel data models using $$\varepsilon $$-contamination: an application to crop yields and climate change
  8. Robust dynamic space–time panel data models using $$ \varepsilon $$-contamination: an application to crop yields and climate change
  9. Handbook of Regression Analysis with Applications in R (Second Edition)
  10. Modeling Structural Breaks in Disturbances Precision or Autoregressive Parameter in Dynamic Model: A Bayesian Approach
  11. Generalized Bayes Estimator for Spatial Durbin Model
  12. Finite sample performance of an estimator of process capability index Cpm for the autocorrelated data
  13. Robust estimation with variational Bayes in presence of competing risks
  14. Forest Cover-Type Prediction Using Model Averaging
  15. Bayesian Estimation and Unit Root Test for Logistic Smooth Transition Autoregressive Process
  16. Robust Bayesian analysis of a multivariate dynamic model
  17. GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS
  18. Robust linear static panel data models usingε-contamination
  19. Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms
  20. Mining SNPs in extracellular vesicular transcriptome ofTrypanosoma cruzi: a step closer to early diagnosis of neglected Chagas disease
  21. Analysis of Panel Data
  22. Bayesian Inference for State Space Model with Panel Data
  23. Statistical process control for autocorrelated data on grid
  24. Bayesian analysis of a linear model involving structural changes in either regression parameters or disturbances precision
  25. Shrinkage estimation in spatial autoregressive model
  26. Bayesian Analysis of Structural Changes in a Linear Regression Model: An Application to Rupee-Dollar Exchange Rate
  27. Modeling Count Data J. M. Hilbe Cambridge Cambridge University Press xvi + 284 pp., $99.00 (hardbound), $37.99 (paperbound) ISBN 978-1-107-02833-3 (hardbound), 978-1-107-61125-2 (paperbound)
  28. Cross-Family Comparative Proteomic Study and Molecular Phylogeny of MAP Kinases in Plants
  29. Cross family comparative proteomic study and molecular phylogeny of MAP kinases in plants
  30. Bayesian Estimation of Regression Coefficients Under Extended Balanced Loss Function
  31. Robust Bayesian analysis of Weibull failure model
  32. Estimation of a subset of regression coefficients of interest in a model with non-spherical disturbances
  33. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus
  34. Confidence ellipsoids based on a general family of shrinkage estimators for a linear model with non-spherical disturbances
  35. Effect of Misspecifying the Disturbance Covariance Matrix on a Family of Shrinkage Estimators
  36. Simultaneous Prediction Based on Shrinkage Estimator
  37. Bayesian Unit Root Test for Time Series Models with Structural Breaks
  38. Bayesian unit root test for model with maintained trend
  39. Appendix: Performance of the 2SHI Estimator Under the Generalised Pitman Nearness Criterion
  40. Risk and Pitman closeness properties of feasible generalized double k-class estimators in linear regression models with non-spherical disturbances under balanced loss function
  41. Unbiased estimation of the MSE matrices of improved estimators in linear regression
  42. Improved Multivariate Prediction in a General Linear Model with an Unknown Error Covariance Matrix
  43. Handbook Of Applied Econometrics And Statistical Inference
  44. Double k-Class Estimators in Regression Models with Non-spherical Disturbances
  45. STEIN-RULE RESTRICTED REGRESSION ESTIMATOR IN A LINEAR REGRESSION MODEL WITH NONSPHERICAL DISTURBANCES
  46. Bayesian analysis of disturbances variance in the linear regression model under asymmetric loss functions
  47. Exact Results on the Inadmissibility of the Feasible Generalized Least Squares Estimator in Regression Models with Non-Spherical Disturbances
  48. Stein rule prediction of the composite target function in a general linear regression model
  49. Operational Variants of the Minimum Mean Squared Error Estimator in Linear Regression Models with Non-Spherical Disturbances
  50. Bayesian Unit Root Test in Nonnormal AR(1) Model
  51. Bayesian estimation for the Pareto income distribution
  52. BAYESIAN ANALYSIS OF THE LINEAR REGRESSION MODEL WITH NON-NORMAL DISTURBANCES
  53. Confidence Sets for the Coefficients Vector of a Linear Regression Model with Nonspherical Disturbances
  54. Bayesian analysis of the linear regression model with an edgeworth series prior distribution
  55. Performance of the 2SHI estimator under the generalised pitman nearness criterion
  56. Robust Bayesian analysis of the linear regression model
  57. Bayesian predictive analysis of the linear regression model with an edgeworth series prior distribution
  58. Selecting a double k-class estimator for regression coefficients
  59. Asymptotic approximations to the gain of the 2shi over stein estimators in linear regression models when the disturbances are small
  60. Ridge regression estimators in the linear regression models with non-spherical errors
  61. On two Sequential Procedures for Estimating the Parameter of a Uniform Distribution
  62. Lindley-like mean correction in the improved estimation of regression models with non-scalar covariance matrix
  63. Comparison of improved regression estimators with and without moments
  64. The necessary and sufficient conditions for the uniform dominance of the two-stage stein estimators
  65. A necessary and sufficient condition for the dominance of an improved family of estimators in linear regression models
  66. Some properties of the distribution of an operational ridge estimator
  67. Estimation of Linear Regression Model with Random Coefficients Ensuring Almost Non‐Negativity of Variance Estimators