dc.description.abstract | Regression analysis (statistical analmodelling) are among statistical methods which
are frequently needed in analyzing quantitative data, especially to model relationship between
response and explanatory variables. Nowadays, statistical models have been developed into
various directions to model various type and complex relationship of data. Rich varieties of
advanced and recent statistical modelling are mostly available on open source software (one of
them is R). However, these advanced statistical modelling, are not very friendly to novice R
users, since they are based on programming script or command line interface. Our research
aims to developed web interface (based on R and shiny), so that most recent and advanced
statistical modelling are readily available, accessible and applicable on web. We have
previously made interface in the form of e-tutorial for several modern and advanced statistical
modelling on R especially for independent responses (including linear models/LM, generalized
linier models/GLM, generalized additive model/GAM and generalized additive model for
location scale and shape/GAMLSS). In this research we unified them in the form of data
analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain
Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory.
The web (interface) make the statistical modeling becomes easier to apply and easier to
compare them in order to find the most appropriate model for the data. | en_US |