martinv13

# This gist demonstrate the use of a linear algorithm to compute exponentially weighted rolling linear regression between two time-series.

# benchmark rolling linear model using R's lm function 
# output 2 regression coefficients + R2, ie 3 value per row
# alpha: decay coefficient (last weight = (1 - alpha) * previous weight)
# miny: minimum number of sample required to calculate an output value

rlm <- function(y, x, alpha, miny=10) {
  
  n <- length(y)

martinv13

library(shiny)

testModuleInput <- function (id) {
  ns <- NS(id)
  uiOutput(ns("inputUI"))
}

testModule <- function (input, output, session, label) {
  ns <- session$ns
  value <- reactiveValues(value="")

martinv13

library(shiny)

appUI <- pageWithSidebar(
  
  # Application title
  headerPanel("New Application"),
  
  sidebarPanel(
    "Progress: ",
    textOutput("counter"),