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cli.md

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    reduce-test.R 843 B
    # Load the package
    library(onlineforecast)
    # Set the data in D to simplify notation
    D <- Dbuilding
    
    
    # Print the first time point
    D$t[1]
    # Set the score period 
    D$scoreperiod <- in_range("2010-12-22", D$t)
    # Plot to see it
    plot(D$t, D$scoreperiod, xlab="Time", ylab="Scoreperiod")
    
    # Exclude other points example
    scoreperiod2 <- D$scoreperiod
    scoreperiod2[in_range("2010-12-30",D$t,"2011-01-02")] <- FALSE
    
    # Generate new object (R6 class)
    model <- forecastmodel$new()
    # Set the model output
    model$output = "heatload"
    # Inputs (transformation step)
    model$add_inputs(Ta = "Ta",
                     mu = "one()")
    # Regression step parameters
    model$add_regprm("rls_prm(lambda=0.9)")
    # Optimization bounds for parameters
    model$add_prmbounds(lambda = c(0.9, 0.99, 0.9999))
    # Set the horizons for which the model will be fitted
    model$kseq <- c(3,18)