Tag: R

Feed: R-bloggers. Author: Gary Hutson. The conference will be held virtually and will kick-off : Monday 8th of November – Wednesday 10th November Featuring: Main Conference Events. This will include more workshops, lightning talks and plenary sessions. And the week before we will have lots of hands-on workshops: Monday 1st November – Friday 5th November Series of workshops for all R levels, including Introduction to R training, package usage and tips and tricks. Further details and how to register will be released shortly. Key note speakers These two influential R contributors: Julia Silge – co-creator of tidytext and now works ... Read More

Feed: R-bloggers. Author: Jakub Sobolewski. Consumer safety and product reliability are top of mind for regulated manufacturing industries, including pharmaceuticals. Documenting key processes, like clinical trials and laboratory tests, is critical and calls for a systematic approach. That’s where GxP comes in, with a strong focus on Good Documentation Practices. This globally recognized standard for quality guidelines and compliance requirements can be further optimized with programmatic solutions offered by R packages. In this article, we’re taking a closer look at how R Markdown and {officedown} can help you create, format, and manage GxP compliant documents with precision and confidence. GxP ... Read More

Feed: R-bloggers. Author: udayan. [This article was first published on R feed, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In computer programming, a variable is a named memory location where data is stored. For example, x = 13.8 Here, x is the variable where the data 13.8 is stored. Now, whenever we use x in our program, we will get 13.8. x = 13.8 # print variable print(x) Output [1] 13.8 As ... Read More

Feed: R-bloggers. Author: sudipb. [This article was first published on R feed, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. R print() Function In R, we use the print() function to print any values and variables. For example, # print values print("R is fun") # print variables x <- "Welcome to Programiz" print(x) Output [1] "R is fun" [1] "Welcome to Programiz" In the above example, we have used the print() function to ... Read More

Feed: R-bloggers. Author: Code R. [This article was first published on Code R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. I started to use R full time for my research about 5 years ago when I started working on my Masters’ thesis and up until today there was one thing missing: proper contour labels. Now, thanks to the wonderful isoband package, I finally got what I wished for and it’s bundled in ... Read More

Feed: R-bloggers. Author: sudipb. [This article was first published on R feed, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Comments are portions of a computer program that are used to describe a piece of code. For example, # declare variable age = 24 # print variable print(age) Here, # declare variable and # print variable are two comments used in the code. Comments have nothing to do with code logic. They do ... Read More

Feed: R-bloggers. Author: sang-heon lee. #========================================================## Quantitative ALM, Financial Econometrics & Derivatives # ML/DL using R, Python, Tensorflow by Sang-Heon Lee ## https://kiandlee.blogspot.com#——————————————————–## Calculate a duration of FRN # using numerical differentiation#========================================================#graphics.off()  # clear all graphsrm(list = ls()) # remove all files from your workspace#——————————————————-# Input#——————————————————-    # continuously compounded zero rate    # zr0 : baseline zero curve    # zru : zero curve generated from 1 bp downward shifted YTM curve    # zrd : zero curve generated from 1 bp upward   shifted YTM curve    str.zero –“month     zr0          zru            zrd                3    0.006594635    0.006694472    0.006494797                6    0.006819495    0.006919243    0.006719675                9    0.00704844    0.007148193    0.006948601                12    0.00731956    0.007419349    0.007219723                15    0.007630967    0.007730765    0.007531127                18    0.00794161    0.008041417    0.007841763                21    0.008232426    0.008332244    0.008132565                24    0.008522513    0.008622352    0.008422642                27    0.008767559    0.008867411    0.008667681                30    0.009012877    0.009112739    0.008912988                33    0.009257467    0.009357346    0.009157564                36    0.00960459    0.009704503    0.009504658″    df.raw – read.table(text = str.zero, header = TRUE)    k  – 4      # interest payment frequency (quarterly)    dr – 0.0001 # yield change (1 bp)#——————————————————-# Calculation of Price and Duration of FRN# by using Numerical Differentiation#——————————————————-    for(t in c(0,1,2)) {        # initialize        df – df.raw        # remaining maturity (monthly)        df$mat – (df$month – t)/12        # interest period        df$tau – df$mat        df$tau[2:12] – df$mat[2:12] – df$mat[1:11]        # discount factor        df$df0  – exp(–df$zr0*df$mat)        df$dfu  – exp(–df$zru*df$mat)        df$dfd  – exp(–df$zrd*df$mat)        # forward rate        df$fd0  – df$zr0        df$fdu  – df$zru        df$fdd  – df$zrd        df$fd0[2:12] – (1/df$tau[2:12])*(df$df0[1:11]/df$df0[2:12]–1)        df$fdu[2:12] – (1/df$tau[2:12])*(df$dfu[1:11]/df$dfu[2:12]–1)        df$fdd[2:12] – (1/df$tau[2:12])*(df$dfd[1:11]/df$dfd[2:12]–1)        # reset the first coupon rate when pricing date is reset date        # assumption of no reset lag        if(t == 0) { # reset date          # newly reset the reference index          r0_reset – 0.00660 # spot rate at spot date          ru_reset – 0.00660           rd_reset – 0.00660        }        # forward rates as cash flows        df$cf0 – df$fd0/k        df$cfu – df$fdu/k        df$cfd – df$fdd/k        # set the first coupon rate        df$cf0[1] – r0_reset/k         df$cfu[1] – ru_reset/k         df$cfd[1] – rd_reset/k         # add nominal principal (1)        df$cf0[nrow(df)] – 1 + df$cf0[nrow(df)]        df$cfu[nrow(df)] – 1 + df$cfu[nrow(df)]        df$cfd[nrow(df)] – 1 + df$cfd[nrow(df)]        # FRN price as sum of discounted variable CF        P0 – sum(df$df0*df$cf0)        Pd – sum(df$dfu*df$cfu)        Pu – sum(df$dfd*df$cfd)        Dr – (Pu–Pd)/(2*dr)/P0      # Duration        # Print        cat(paste0(“nResults for FRN (t=”,t,“)nn”,                   “Price     = “, P0, “n”,                   “Duration  = “, Dr, “n”,                   “time to the first next payment daten”,                   ”          = “, (3–t)/12, “nn”))    } ... Read More

Feed: R-bloggers. Author: Bluecology blog. [This article was first published on Bluecology blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. ShareTweet My course notes for “Current approaches to Species Distribution Modelling in R “ for World Fisheries Congress 2021 are now free online. The course covers tidyverse and sf workflows for models, a beginners intro to modelling options and how to make spatial predictions. There’s also bonus tutorial on the course site ... Read More

Feed: R-bloggers. Author: Ly Thien. Have you ever spent the whole day applying different Machine Learning (ML) algorithms from several libraries, coping with a legion of conditional and unconditional hyperparameters, and attempting to deal with different data processing techniques? Undeniably, it is a try-and-error work with prerequisite experience. These repeatable trials can be very time-consuming and arduous, even for skilled ML practitioners.To tackle those aforementioned problems, with the rapidity in building models and a user-friendly interface without requiring any advanced prior knowledge in Data Science; the AutoML R forester package has become a shining candidate to be considered.Why are AutoML ... Read More

Feed: R-bloggers. Author: sang-heon lee. [This article was first published on K & L Fintech Modeling, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. The price of a floating rate bond is always equal to the face value at the payment dates and the duration is the remaining time until the first next reset date. This post explains these arguments by using some heuristic derivations and R code. Floating rate bond or note ... Read More