Timezone conversion is a common practice in real world and the simplest way is to utilize build-in functions in R rather than design your owns functions to take care of the hour offset, especially in Read More ... [Read more...]

I often have to read a lot of datasets at once using R. So I’ve wrote the following function to solve this issue:

read_list <- function(list_of_datasets, read_func){

        read_and_assign <- function(dataset, read_func){
                dataset_name <- as.name(dataset)
                dataset_name <- read_func(dataset)
        }

        # invisible is used to suppress the unneeded output
        output <- invisible(
                sapply(list_of_datasets,
                           read_and_assign, read_func = read_func, simplify = FALSE, USE.NAMES = TRUE))

        # Remove the extension at the end of the data set names
        names_of_datasets <- c(unlist(strsplit(list_of_datasets, "[.]"))[c(T, F)])
        names(output) <- names_of_datasets
        return(output)
}

You need to supply a list of datasets as well as the function to read the datasets to read_list. So for example to read ... [Read more...]

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I often have to read a lot of datasets at once using R. So I’ve wrote the following function to solve this issue:

read_list <- function(list_of_datasets, read_func){

        read_and_assign <- function(dataset, read_func){
                dataset_name <- as.name(dataset)
                dataset_name <- read_func(dataset)
        }

        # invisible is used to suppress the unneeded output
        output <- invisible(
                sapply(list_of_datasets,
                           read_and_assign, read_func = read_func, simplify = FALSE, USE.NAMES = TRUE))

        # Remove the extension at the end of the data set names
        names_of_datasets <- c(unlist(strsplit(list_of_datasets, "[.]"))[c(T, F)])
        names(output) <- names_of_datasets
        return(output)
}

You need to supply a list of datasets as well as the function to read the datasets to read_list. So for example to read ... [Read more...]

Microsoft R Open 3.3.0, the enhanced distribution of open source R, is now available for download for Windows, Mac and Linux systems. This release includes a significant updates to the R language engine from the R Core Group bundled with the multithreaded performance and CRAN package time-machine capabilities of Microsoft R ... [Read more...]

A key – but challenging – part of learning to program is moving from writing technically-correct code “that works” to writing high-quality code that is sensibly decomposed into functions, generically-applicable and generally “good”. Indeed, you could say that this is exactly what Software Carpentry is about – taking you from someone bodging together ... [Read more...]

Updated on 25 August 2017Preamable: Predictions using dynamic modellingMachine Learning and  Neural Networks are not the only way to do data science or AI. There are other techniques to explore  , for example, from quantitative economics. Apart from Game Theory, dynamic modelling could be suitable to many prediction problems, specially the ones ... [Read more...]

Econometrics aims at estimating observables in the economy and their inter-dependencies and testing the estimates against the economic reality. A quantitative approach to express these inter-dependencies appear as simultaneous equations, an i.e. system of linear equations, this is  a mathematical structure of economic relationships that were made possible with ... [Read more...]

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Computing platforms should be like Lego. That is, they should provide the fundamental building blocks and enable the users' imagination to innovate. The latest issue of Stata Journal exemplifies how Stata and, by the same account, R provide the platform for the users to innovate beyond the innate capacity of ... [Read more...]

Computing platforms should be like Lego. That is, they should provide the fundamental building blocks and enable the users' imagination to innovate. The latest issue of Stata Journal exemplifies how Stata and, by the same account, R provide the platform for the users to innovate beyond the innate capacity of ... [Read more...]

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The second Armadillo release of the 7.* series came out a few weeks ago: version 7.200.2. And RcppArmadillo version 0.7.200.2.0 is now on CRAN and uploaded to Debian. This followed the usual thorough reverse-dependecy checking of by now over 240 pac... [Read more...]

I been updating some existing packages and github-releasing new ones (before a CRAN push). Most are “cyber”-related, but there are some general purpose ones. Here’s a quick overview: docxtractr (CRAN, now, v0.2.0) was initially designed to make it easy to get data tables out of MS Word (docx) ... [Read more...]

After many years of hard work I’m thrilled to announce that the collaborative research project Michael Dreiling and I began in 2000 has been published with Cambridge University Press! Our book, Agents of Neoliberal Globalization can be purchased dir... [Read more...]

A few months ago I set out to write an R package for accessing the Maps API with my employer’s (paid) Google for Work/Premium account. At the time, I was unable to find an R package that could generate the encrypted signature, send the URL to Google... [Read more...]

Crop rotation is an agricultural production practice to increase yield, mitigate disease, and control pests. This production practice involves growing crops in specific sequences to improve the quality of soil for the following crop. A common example in the United States is the practice of growing soybeans before corn. In ... [Read more...]