wrMisc: searchLinesAtGivenSlope – R documentation

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searchLinesAtGivenSlope

Search points forming lines at given slope

Description

searchLinesAtGivenSlope searchs among set of points (2-dim) those forming line(s) with user-defined slope ('coeff'), ie search optimal (slope-) offset parameter(s) for (regression) line(s) with given slope ('coef'). Note: larger data-sets : segment residuals to 'coeff' & select most homogenous

Usage

searchLinesAtGivenSlope(
  dat,
  coeff = 1.5,
  filtExtr = c(0, 1),
  minMaxDistThr = NULL,
  lmCompare = TRUE,
  indexPoints = TRUE,
  displHist = FALSE,
  displScat = FALSE,
  bestCluByDistRat = TRUE,
  neighbDiLim = NULL,
  silent = FALSE,
  debugM = FALSE,
  callFrom = NULL
)

Arguments

`dat`	matrix or data.frame
`coeff`	(numeric) slope to consider
`filtExtr`	(integer) lower & upper quantile values, remove points with extreme deviation to offset=0, (if single value: everything up to or after will be used)
`minMaxDistThr`	(logical) optional minumum and maximum distance threshold
`lmCompare`	(logical) add'l fitting of linear regression to best results, return offset AND slope based on lm fit
`indexPoints`	(logical) return results as list with element 'index' specifying retained points
`displHist`	(logical) display histogram of residues
`displScat`	(logical) display (simple) scatter plot
`bestCluByDistRat`	(logical) initial selection of decent clusters based on ratio overallDist/averNeighbDist (or by CV & cor)
`neighbDiLim`	(numeric) additional threshold for (trimmed mean) neighbour-distance
`silent`	(logical) suppress messages
`debugM`	(logical) for bug-tracking: more/enhanced messages
`callFrom`	(character) allow easier tracking of message(s) produced

Value

matrix of line-characteristics (or if indexPoints is TRUE then list (line-characteristics & index & lm-results)

Examples

set.seed(2016); ra1 <- runif(300)
 dat1 <- cbind(x=round(c(1:100+ra1[1:100]/5,4*ra1[1:50]),1),
  y=round(c(1:100+ra1[101:200]/5,4*ra1[101:150]),1))
(li1 <- searchLinesAtGivenSlope(dat1,coeff=1))

wrMisc

Analyze Experimental High-Throughput (Omics) Data

v1.5.4

GPL-3

Authors

Wolfgang Raffelsberger [aut, cre]

Initial release