# NOT RUN {
## Load rSCA package
library(rSCA)
## X data file
xdata <- c("A B C D\r", "0.095 0.044 39.9 27\r",
"0.810 0.058 9.1 8\r", "0.101 0.077 11.4 14\r",
"0.006 0.141 20.5 29\r", "0.070 0.281 27.3 26\r",
"0.481 0.514 30.2 48\r", "0.120 0.286 36.4 39\r",
"0.480 0.199 40.9 27\r", "0.112 0.101 29.9 18\r",
"0.026 0.203 48.1 28\r", "0.128 1.235 48.2 61\r",
"2.681 0.439 51.1 98\r", "1.601 0.333 56.1 99\r",
"1.398 0.455 19.3 103\r", "1.256 0.314 14.9 17\r",
"2.618 0.609 9.1 19\r", "1.217 0.880 17.2 73\r",
"1.411 2.115 19.6 203\r", "0.245 6.839 49.2 296\r",
"0.724 3.060 17.1 192\r", "0.019 2.252 29.1 123\r",
"1.321 5.730 41.1 288\r", "0.903 3.078 39.0 97\r",
"0.714 1.013 16.7 5\r", "0.581 1.398 11.7 57\r",
"0.080 1.734 10.2 52\r", "0.120 1.848 6.6 132\r",
"0.089 1.357 10.3 148\r", "0.112 0.585 19.3 79\r",
"0.192 0.675 6.9 39\r", "0.301 1.937 11.9 6\r")
xdatafile <- tempfile()
writeLines(xdata, xdatafile)
## Y data file
ydata <- c("Y1 Y2 Y3\r", "0.020 0.034 10.01\r",
"0.011 0.011 6.92\r", "0.016 0.018 9.53\r",
"0.022 0.018 5.04\r", "0.031 0.029 8.90\r",
"0.057 0.036 9.98\r", "0.040 0.048 12.96\r",
"0.061 0.050 9.84\r", "0.023 0.031 8.84\r",
"0.025 0.020 4.66\r", "0.041 0.042 9.02\r",
"0.070 0.029 11.37\r", "0.077 0.022 11.88\r",
"0.105 0.038 11.06\r", "0.038 0.027 11.64\r",
"0.058 0.019 8.25\r", "0.051 0.050 10.01\r",
"0.073 0.038 9.20\r", "0.123 0.080 9.91\r",
"0.089 0.046 9.37\r", "0.073 0.039 7.99\r",
"0.139 0.069 13.28\r", "0.095 0.048 9.80\r",
"0.034 0.040 8.50\r", "0.055 0.034 9.21\r",
"0.020 0.050 8.67\r", "0.070 0.036 8.03\r",
"0.058 0.039 8.01\r", "0.057 0.031 6.30\r",
"0.050 0.014 7.92\r", "0.039 0.040 8.08\r")
ydatafile <- tempfile()
writeLines(ydata, ydatafile)
## New X data
xnewdata <- c("A B C D\r", "0.085 0.054 35.9 29\r",
"0.820 0.068 9.2 7\r", "0.121 0.067 12.4 13\r",
"0.016 0.151 21.5 24\r", "0.075 0.283 25.3 16\r",
"0.581 0.524 31.2 38\r", "0.130 0.486 33.4 36\r")
xnewdatafile <- tempfile()
writeLines(xnewdata, xnewdatafile)
## Modeling the relationship between Y and X with SCA
myModel = rSCA.modeling(xfile = xdatafile, yfile = ydatafile,
x.col.names = TRUE, y.col.names = TRUE)
## Predict Y with the SCA model
rSCA.inference(xfile = xnewdatafile, x.col.names = TRUE, model = myModel)
## Perform multiple predictions based on a previously-trained model
## Step 1. Construct a model based on previous tree and map files:
## >> preModel = list(treefile = path_to_tree_file, mapfile = path_to_map_file, type = "mean")
## Note that the value for the parameter of "type" should be the same as what you
## used in the previous traning
## Step 3. Perform multiple predictions with different xfiles
## >> rSCA.inference(xfile = xnewdatafile_1, x.col.names = TRUE, model = preModel)
## >> rSCA.inference(xfile = xnewdatafile_2, x.col.names = TRUE, model = preModel)
# }
Run the code above in your browser using DataLab