Category: Learning modules
In statistics, to increase the prediction accuracy and interpret-ability of the model, LASSO (Least Absolute Shrinkage and Selection Operator) is extremely popular. It is a regression procedure that involves selection and regularisation and was developed in 1989. Lasso regression is an extension of linear regression that uses shrinkage. The lasso imposes a constraint on the sum of the absolute values of the model parameters. Here the sum has a specific constant as an upper bound.
exploratory model analysis, regressions in supervised learning, Supervised learningStructural equation model is a statistical modeling technique. Structural equation model (SEM) tests estimate or establish relationships between variables. It is a multivariate statistical data analysis technique. SEM analyzes the structural relationships or to establish causal relationships between variables.
SEM moduleThis article explains how to test ARIMA models and identifies the appropriate one for the process of forecasting time series GDP.
empirical analysis with econometrics, STATA for data analysis, time series analysis, time series for econometrics, trend analysisMissing data is one of the most common problems in almost all statistical analyses. If the data is not available for all the observations of variables in the model, then it is a case of ‘missing data’.
estimation in supervised learning, Supervised learning, trend analysisMarkov chain is one of the most important tests in order to deal with independent trials processes. There are two major principal theorems for these processes. The first one is the ‘Law of Large Numbers’ and the second one is the ‘Central Limit Theorem’.
estimation in supervised learning, Supervised learningBootstrap and jackknife are superficially similar statistical techniques that involve re-sampling the data. They are nonparametric and specific resampling techniques that can estimate standard errors and confidence intervals of a population parameter.
estimation in supervised learning, Supervised learningAutoregressive Integrated Moving Average (ARIMA) is popularly known as Box-Jenkins method. The emphasis of this method is on analyzing the probabilistic or stochastic properties of a single time series. Unlike regression models where Y is explained by X1 X2….XN regressor (like the introductory case where GDP is explained by GFC and PFC), ARIMA allows Y (GDP) to be explained by its own past or lagged values.
empirical analysis with econometrics, STATA for data analysis, time series analysis, time series for econometricsNeural network, popularly known as Artificial Neural Network (ANN) is an information processing system with a large number of nodes and connections as part of a structure which helps in processing complex information.
regressions in supervised learning, Supervised learning, trend analysis