Title: Download and Manage Data from Tehran Stock Exchange
Description: Tools for downloading and organizing data from Tehran Stock Exchange (TSE) <http://new.tse.ir/en/>. It also performs some descriptive data analysis for assets.

Title: Manage Data from Stock Exchange Markets
Description: Tools to perform some descriptive data analysis for assets. Manage the portfolio and capital of assets. It also downloads and organizes data from the Tehran Stock Exchange (TSE).

Title: Total Survey Error Under Multiple, Different Weighting Schemes
Description: Calculates total survey error (TSE) for a survey under multiple, different weighting schemes, using both scale-dependent and scale-independent metrics.  Package works directly from the data set, with no hand calculations required: just upload a properly structured data set (see TESTWGT and its documentation), properly input column names (see functions documentation), and run your functions.  For more on TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) <doi:10.1093/poq/nfq058>; Biemer, Paul et.al. (2017, ISBN:9781119041672); etc.
Note: 'TSEwgt' is a companion package to 'TSE'. Each package calculates
TSE, but the former for multiple, different surveys, and the
latter for a single survey under multiple, different weighting

Title: Two Stage Forecasting (TSF) for Long Memory Time Series in
Author: Sandipan Samanta, Ranjit Kumar Paul and Dipankar Mitra
Maintainer: Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
Description: Forecasting of long memory time series in presence of structural break by using TSF algorithm by Papailias and Dias (2015) <doi:10.1016/j.ijforecast.2015.01.006>.
Packaged: 2017-07-15 06:50:30 UTC; ranjitstat

Title: Trait Specific Gene Selection using SVM and GA
c(person("Md. Samir", "Farooqi", email = "ms.Farooqi@icar.gov.in", role = "aut"),
person("K.K.", "Chaturvedi", email = "kk.Chaturvedi@icar.gov.in", role = "aut"),
person("D.C.", "Mishra", email = "Dwijesh.Mishra@icar.gov.in", role = "aut"),
person("Sudhir", "Srivastava", email = "Sudhir.Srivastava@icar.gov.in", role = c("cre","aut")))
Description: Obtaining relevant set of trait specific genes from gene expression data is important for clinical diagnosis of disease and discovery of disease mechanisms in plants and animals. This process involves identification of relevant genes and removal of redundant genes as much as possible from a whole gene set. This package returns the trait specific gene set from the high dimensional RNA-seq count data by applying combination of two conventional machine learning algorithms, support vector machine (SVM) and genetic algorithm (GA). GA is used to control and optimize the subset of genes sent to the SVM for classification and evaluation. Genetic algorithm uses repeated learning steps and cross validation over number of possible solution and selects the best. The algorithm selects the set of genes based on a fitness function that is obtained via support vector machines. Using SVM as the classifier performance and the genetic algorithm for feature selection, a set of trait specific gene set is obtained.
Imports: caret, edgeR, fastmatch, genalg, kernlab, e1071