interpolate: Time Series Interpolation

Description Usage Arguments Details Value Examples

View source: R/interpolate.R

Description

Wrapper function to interpolate a time series. If groups are specified, each group is processed separately. The time points of each group are supposed to be in chronological order.

Usage

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interpolate(x, interval = NA, time.index = NA, time.vector = c(),
  method = "stineman", groups = c(), negzero = FALSE)

Arguments

x

the time series matrix, rows are objects and columns are time points

interval

the target intervals to be present after interpolation

time.index

the row index holding time points

time.vector

the vector holding time points

method

fmm, periodic, natural, hyman or monoH.FC (spline), scaledstineman, stineman or parabola (stinterp)

groups

a vector with group assignments and as many entries as there are samples

negzero

set negative values (can be introduced by interpolation) to zero

Details

If no interval is provided, the intervals in the time vector are computed and the most frequent one is taken as the interval. The default interpolation method is stineman. Note that interpolation can introduce negative values in the abundance matrix.

Value

interpolated time series

Examples

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  data("david_stoolA_otus")
  data("david_stoolA_metadata")
  days=david_stoolA_metadata[1,]
  sorted=sort(apply(david_stoolA_otus,1,sum),decreasing=TRUE,index.return=TRUE)
  davida.top=david_stoolA_otus[sorted$ix[1:100],]
  tsplot(interpolate(davida.top,time.vector=days))

hallucigenia-sparsa/seqtime documentation built on Oct. 25, 2018, 2:12 p.m.