R: Compute Several Deviance Measures for Comparison

compareME {qualV} | R Documentation

## Compute Several Deviance Measures for Comparison

### Description

Various deviance measures are computed allowing the user to find the aspects in which two time series differ.

### Usage

    compareME(o, p,
              o.t      = seq(0, 1, length.out = length(o)),
              p.t      = seq(0, 1, length.out = length(p)),
              ignore   = c("raw", "centered", "scaled", "ordered"),
              geometry = c("real", "logarithmic", "geometric", "ordinal"),
              measure  = c("mad", "var", "sd"),
              type     = "normalized",
              time     = "fixed", ..., col.vars=c("time", "ignore")
             )
    ## S3 method for class 'compareME'
    print(x, ..., digits = 3)
    ## S3 method for class 'compareME'
    summary(object, ...)

### Arguments

`o` | vector of observed values,
`p` | vector of predicted values,
`o.t` | vector of observation times,
`p.t` | vector of times for predicted values,
`ignore` | a subset of `c("raw", "centered", "scaled", "ordered")` as defined in `generalME` to specify the aspects of the data to be ignored,
`geometry` | a subset of `c("real", "logarithmic", "geometric", "ordinal")` as defined in `generalME` to specify the geometry of the observed data,
`measure` | a subset of `c("mad", "var", "sd")` to specify the type of error to be measured,
`type` | a subset of `c("dissimilarity", "normalized", "similarity", "reference")` as defined in `generalME` to specify the type of deviance measure to be used,
`time` | a subset of `c("fixed", "transform")`, indicates wether the time should actually be transformed. If this argument and the time arguments are missing the comparison is based on values only without time matching.
`...` | further arguments passed to `timeTransME`,
`col.vars` | a subset of `c("ignore", "geometry", "measure", "time")` to be displayed in the columns of the resulting `ftable`,
`digits` | number of significant digits displayed,
`x, object` | objects of class `compareME`.

### Details

The function provides a simple standard interface to get a first idea on the similarities and dissimilarities of two time series spanning the same time interval. The `print` and `summary` methods extract the relevant information, rounded to an optional number of significant digits.

### Value

The result is a list of `ftable`s containing the deviance measures of all requested combinations of parameters. The list is done over the different types of measures requested.

### See Also

`timeTransME`, `generalME`

### Examples

    # a constructed example
    x <- seq(0, 2*pi, 0.1)
    y <- 5 + sin(x)             # a process
    o <- y + rnorm(x, sd = 0.2) # observation with random error
    p <- y + 0.1                # simulation with systematic bias

    os <- ksmooth(x, o, kernel = "normal",
      bandwidth = dpill(x, o), x.points = x)$y
    plot(x, o); lines(x, p); lines(x, os, col = "red")

    compareME(o, p)
    compareME(os, p)

    # observed and measured data with non-matching time intervals
    data(phyto)
    compareME(obs$y, sim$y, obs$t, sim$t, time = "fixed")
    tt <- timeTransME(obs$y, sim$y, obs$t, sim$t, ME = SMSLE, trials = 5)
    compareME(tt$yo, tt$yp)

    # show names of deviance measures
    compareME(type = "name")

[Package qualV version 0.3-3 Index]