inst/unitTests/runit.TermPlots.R

In fRegression: Rmetrics - Regression Based Decision and Prediction

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# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
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# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA  02111-1307  USA


################################################################################
# FUNCTION:                 REGRESSION TERM PLOTS
#  termPlot                  Line Plot
#  termPersp                 Perspective Plot
#  termContour               Contour Plot
################################################################################


test.termPlot <-
    function()
{

    x <- regSim(model = "LM3", n = 100)
    lmfit <- regFit(Y ~ X1 + X2 + X3, data = x, use = "lm")


    # Simulate Data - a data frame:
    DATA <- regSim(model = "GAM3", n = 100)
    utils::head(DATA)
    class(DATA)

    # Convert to a timeSeries object:
    DATATS <- as.timeSeries(DATA)
    utils::head(DATATS)
    class(DATATS)
    
    require(mgcv)
    
    # Fit:
    LM    = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "lm")
    RLM   = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "rlm")
    AM    = regFit(Y ~ 1 + X1 + X2 + X3,   DATATS, use = "gam")
    PPR   = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr")
    PPR4  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr", nterms = 4)
    POLYMARS = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "polymars")
    NNET  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet")
    NNET6 = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet", size = 6)
    
    ## TODO: Term Plot:
    ## par(ask = FALSE)
    ## par(mfrow = c(1, 1))
    ## termPlot(LM)
    ## termPlot(RLM)
    ## termPlot(AM)
    ## termPlot(PPR)
    ## termPlot(POLYMARS)
    ## termPlot(NNET)

    ## TODO:
    ## par(ask = FALSE)
    ## par(mfrow = c(1, 1))
    ## termPlot(LM, terms = "X1")
    ## termPlot(RLM, terms = "X1")
    ## termPlot(AM, terms = "X1")
    ## termPlot(PPR, terms = "X1")
    ## termPlot(PPR4, terms = "X1")
    ## termPlot(POLYMARS, terms = "X1")
    ## termPlot(NNET, terms = "X1")
    ## termPlot(NNET6, terms = "X1")

    # Return Value:
    return()
}


# ------------------------------------------------------------------------------


test.termPersp <-
    function()
{
    # Simulate Data - a data frame:
    DATA <- regSim(model = "GAM3", n = 100)
    utils::head(DATA)
    class(DATA)
    # Convert to a timeSeries object:
    DATATS <- as.timeSeries(DATA)
    utils::head(DATATS)
    class(DATATS)
    
    require(mgcv)
    
    # Fit:
    LM    = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "lm")
    RLM   = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "rlm")
    AM    = regFit(Y ~ 1 + s(X1)+s(X2)+s(X3),   DATATS, use = "gam")
    PPR   = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr")
    PPR4  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr", nterms = 4)
    POLYMARS = regFit(Y ~ X1 + X2 + X3,  data = DATATS, use = "polymars")
    NNET  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet")
    NNET6 = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet", size = 6)
    
    ## TODO:  Bivariate Perspective Term Plot:
    ## par(ask = FALSE)
    ## par(mfrow = c(1, 1))
    ## termPersp(LM,    terms = c("X1", "X2"))
    ## termPersp(RLM,   terms = c("X1", "X2"))
    ## termPersp(AM,    terms = c("X1", "X2"))
    ## termPersp(PPR,   terms = c("X1", "X2"))
    ## termPersp(PPR4,  terms = c("X1", "X2"))
    ## termPersp(POLYMARS, terms = c("X1", "X2"))
    ## termPersp(NNET,  terms = c("X1", "X2"))
    ## termPersp(NNET6, terms = c("X1", "X2"))
    
    # Return Value:
    return()
}


# ------------------------------------------------------------------------------


test.termContour <-
    function()
{

    # Simulate Data - a data frame:
    DATA = regSim(model = "GAM3", n = 100)
    utils::head(DATA)
    class(DATA)
    # Convert to a timeSeries object:
    DATATS = as.timeSeries(DATA)
    utils::head(DATATS)
    class(DATATS)
    
    require(mgcv)
    
    # Fit:
    LM    = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "lm")
    RLM   = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "rlm")
    AM    = regFit(Y ~ 1 + s(X1)+s(X2)+s(X3),   DATATS, use = "gam")
    PPR   = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr")
    PPR4  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "ppr", nterms = 4)
    POLYMARS = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "polymars")
    NNET  = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet")
    NNET6 = regFit(Y ~ X1 + X2 + X3,     data = DATATS, use = "nnet", size = 6)
    
    ## TODO: Bivariate Contour Term Plot:
    ## par(ask = FALSE)
    ## par(mfrow = c(1, 1))
    ## termContour(LM,    terms = c("X1", "X2"))
    ## termContour(RLM,   terms = c("X1", "X2"))
    ## termContour(AM,    terms = c("X1", "X2"))
    ## termContour(PPR,   terms = c("X1", "X2"))
    ## termContour(PPR4,  terms = c("X1", "X2"))
    ## termContour(POLYMARS, terms = c("X1", "X2"))
    ## termContour(NNET,  terms = c("X1", "X2"))
    ## termContour(NNET6, terms = c("X1", "X2"))
    
    # Return Value:
    return()
}


# ------------------------------------------------------------------------------


test.termComparison <- 
    function()
{
    # Simulate Data - a data frame:
    DATA = regSim(model = "GAM3", n = 100)
    utils::head(DATA)
    class(DATA)
    
    # Convert to a timeSeries object:
    DATATS = as.timeSeries(DATA)
    utils::head(DATATS)
    class(DATATS)
    
    require(mgcv)
    
    ## TODO:
    if (FALSE) {
    
        # Comparison:
        par(ask = FALSE)
        par(mfrow = c(1, 1))
    
        LM = regFit(Y ~ 1 + X1 + X2 + X3, data = DATATS, use = "lm")
        termPlot(LM)
    
        AM = regFit(Y ~ 1 + s(X1)+s(X2)+s(X3), data = DATATS, use = "gam")
        termPlot(AM)
        am = gam(formula = Y ~ s(X1) + s(X2) + s(X3), data = DATA)
        for (s in 1:3) {
            plot(am, residuals = residuals(am), se = TRUE,
                main = "AM", cex = 0.7, select = s, pch = 19); grid()
        }
    }

    # Return Value:
    return()
}


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