Modelling time-varying mobility flows using function-to-function regression: Analysis of a bike sharing system in the city of Milan |
540:S |
QCAS / 68 / 5-6 / 411 |
Subsampling from features in large regression to find “winning features” |
540:Y |
QCAS / 68 / 1-2 / 103 |
Empirical likelihood for outlier detection in regression models |
540:Y |
QCAS / 65 / 1-2 / 97 |
Adaptive Monte Carlo for Bayesian variable selection in regression models |
540:Y |
QCAS / 59 / 5-6 / 519 |
Optimal designs for regression models with a constant coefficient of variation |
540:Y |
QCAS / 59 / 5-6 / 521 |
Uniform inference in predictive regression models |
540:Y |
QCAS / 59 / 5-6 / 523 |
Optimal discriminating designs for several competing regression models |
540:Y |
QCAS / 59 / 1-2 / 131 |
Optimal designs for quantile regression models |
540:Y |
QCAS / 58 / 5-6 / 541 |
Subsample ignorable likelihood for regression analysis with missing data |
540:Y |
QCAS / 58 / 1-2 / 105 |
A truncated logistic regression model in probability of
detection evaluation |
540:Y |
QCAS / 58 / 1-2 / 109 |
Fitting regression models with response–biased samples |
540:Y |
QCAS / 58 / 1-2 / 111 |
Diagnostics analysis for log-Birnbaum-Saunders regression models with censored data |
540:Y |
QCAS / 57 / 3 / 255 |
The prediction properties of classical and inverse regression for the simple linear calibration problem |
540:Y |
QCAS / 57 / 1-2 / 103 |
Approximate tolerance limits under log-location-scale regression models in the presence of censoring |
540:Y |
QCAS / 56 / 3 / 251 |
A comparison of maximum likelihood and median-rank regression for Weibull estimation |
540:Y |
QCAS / 56 / 1-2 / 115 |
How many studies do you need? A primer on statistical power for meta-analysis |
540:Y |
QCAS / 56 / 1-2 / 117 |
A noncentral t regression model for meta-analysis |
540:Y |
QCAS / 56 / 1-2 / 121 |
Sampling bias and logistic models |
540:Y |
QCAS / 54 / 1-2 / 103 |
Projection density estimation under an m-sample semiparametric model |
540:Y |
QCAS / 53 / 6 / 595 |
Fitting logistic regression models with contaminated case-control data |
540:Y |
QCAS / 52 / 3 / 329 |
Bias-corrected maximum semiparametric likelihood estimation under logistic regression models based on case-control data |
540:Y |
QCAS / 51 / 4 / 427 |
A sequential approach to testing seasonal unit roots in high frequency data |
540:Y |
QCAS / 51 / 3 / 323 |
Regression analysis of interval-censored failure time data with linear transformation models |
540:Y |
QCAS / 51 / 1 / 81 |
Estimating equation approach for regression analysis of failure time data in the presence of interval-censoring |
540:Y |
QCAS / 51 / 1 / 83 |
Using logistic regression to evaluate new lid designs |
540:Y |
QCAS / 50 / 1 / 79 |
Nonparametric regression analysis of uncertain and imprecise data using belief functions |
540:Y |
QCAS / 49 / 6 / 677 |
Censored generalized Poisson regression model |
540:Y |
QCAS / 49 / 6 / 679 |
Empiricial study of QS-9000 using principal component analysis and robust regression |
540:Y |
QCAS / 49 / 5 / 567 |
Finite sample properties for the semiparametric estimation of the intercept of a censored regression model |
540:Y |
QCAS / 49 / 5 / 571 |
Regression with response distributions of Pareto-type |
540:Y |
QCAS / 49 / 2 / 205 |
A comparison of partial least squares regression with other prediction methods |
540:Y |
QCAS / 49 / 1 / 89 |
Robust stepwise regression |
540:Y |
QCAS / 48 / 5 / 557 |
Regression estimators in extreme and median ranked set samples |
540:Y |
QCAS / 47 / 5 / 553 |
Asymmetric confidence bands for simple linear regression over bounded intervals |
540:Y |
QCAS / 46 / 5 / 575 |
A cautionary note about assessing the fit of logistic regression models |
540:A |
QCAS / 45 / 2 / 203 |
Markov Poisson regression models for discrete time series. Part 2: Applications. |
540:Y |
QCAS / 45 / 2 / 205 |