hzar.makeCline1DFreq: Make a cline model with the requested attributes.
In GrahamDB/hzar: Hybrid Zone Analysis using R

Description Usage Arguments Details Value Author(s) References See Also Examples

Constructs a clineMetaModel object for use with hzar.first.fitRequest.old.ML. Said object can be further tailored to the specific model desired, or can be used as-is.

hzar.makeCline1DFreq(data = NULL, scaling = "none", tails = "none",
  direction = NULL) 
hzar.makeCline1DCLT(data = NULL, scaling = "free", tails = "none",
  direction = NULL)
hzar.makeCline1DNormal(data, tails = "none")

`data`	A `hzar.obsData` object, used to determine cline direction and estimate initial values.
`scaling`	Can be one of three strings: "none"A model with fixed minimum value 0 and maximum value 1 is desired. "fixed"A model with minimum and maximum values fixed to the minimum and maxumimum observed mean values of `data` is desired. "free"A model with the minimum and maximum value as free parameters is desired.
`tails`	Can be one of five strings: "none"A model with no exponential tails is desired "right"A model with just one exponential tail on the right is desired. "left"A model with just one exponential tail on the left is desired. "mirror"A model with two exponential tails mirrored about the cline center is desired. "both"A model with two tails with independent parameters is desired.
`direction`	Can be one of three values: NULLDetermine direction using `data` "ascending"A model whose estimates increase as the site distance increases is desired. "descending"A model whose estimates decrease as the site distance increases is desired.

The clineMetaModel object returned by hzar.makeCline1DNormal has a slightly diffent structure, due to the complexity of the normal cline model. Use hzar.first.fitRequest.gC instead of hzar.first.fitRequest.old.ML to construct the hzar.fitRequest object needed for hzar.doFit.

A clineMetaModel object, which is a list with the following 4 components:

`req`	A boolean function of the model parameters w
`prior`	Description of 'comp1'
`func`	Description of 'comp1'
`parameterTypes`	A list of `clineParameter` objects, named with the parameter names. A `clineParameter` object structure: Components: valThe initial or fixed value. wThe parameter tuning. Attributes: "param"The parameter name. "fixed"TRUE if the parameter is fixed. "limit.lower"The parameter minimum finite value. "limit.upper"The parameter maximum finite value. "realBTWN01"The parameter is restricted to between 0 and 1.

Graham Derryberry asterion@alum.mit.edu

Gay, L., P.-A. Crochet, D. A. Bell, and T. Lenormand. 2008. Comparing clines on molecular and phenotypic traits in hybrid zones: a window on tension zone models. Evolution 62:2789-2806.

Szymura, J., and N. H. Barton. 1986. Genetic analysis of a hybrid zone between the fire-bellied toads, Bombina bombina and B. variegata, near Cracow in souhern Poland. Evolution 40:1141-1159.

Szymura, J., and N. H. Barton. 1991. The genetic structure of the hybrid zone between the fire-bellied toads Bombina bombina and B. variegata: comparisons between transects and between loci. Evolution 45:237-261.

hzar.obsData Locality based observed data. hzar.doNormalData1DRaw Individual observed data. hzar.doMorphoSets Bernouilli transformed individual observed data.

hzar.model.addBoxReq Adding model requirements. hzar.first.fitRequest.old.ML hzar.first.fitRequest.gC

data(manakinMolecular);
mknAdaA <-
  hzar.doMolecularData1DPops(manakinMolecular$distance,
                             manakinMolecular$ada.A,
                             manakinMolecular$ada.nSamples);
mknAdaAm <-
  hzar.makeCline1DFreq(mknAdaA, scaling="fixed",tails="none");
str(mknAdaAm);
## compile using this method:
mknAdaAFR <-
hzar.first.fitRequest.old.ML(model=mknAdaAm, obsData=mknAdaA)
hzar.plot.cline(mknAdaAFR)

data(manakinMorphological)
data(manakinLocations)
mknCCbt <-
  hzar.doMorphoSets("collar.color",
                    tDist=manakinLocations,
                    tDLocCol="LocalityID",
                    tDDistCol="distance",
                    tValues=manakinMorphological,
                    tVLocCol="Locality")$collar.color
mknCCbtM <-
  hzar.makeCline1DFreq(mknCCbt, scaling="fixed",tails="none");
str(mknCCbt);
## compile using this method:
mknCCbtFR <-
  hzar.first.fitRequest.old.ML(model=mknCCbtM, obsData=mknCCbt)
hzar.plot.cline(mknCCbtFR)

data(manakinMorphological);
data(manakinLocations);
mknBLg <-
  hzar.doNormalData1DRaw(
    hzar.mapSiteDist(siteID=manakinLocations$LocalityID,
                     distance=manakinLocations$distance),
    traitSite=manakinMorphological$Locality,
    traitValue=manakinMorphological$beard.length)
hzar.plot.obsData(mknBLg)
mknBLgM <-
  hzar.makeCline1DNormal(mknBLg, tails="none");

## Emulate scaling="fixed"

hzar.meta.fix(mknBLgM)$muL <- TRUE
hzar.meta.fix(mknBLgM)$muR <- TRUE
## Use variance of site at the left (site A) and right (site L). 
hzar.meta.init(mknBLgM)$varL<-mknBLg$frame["A","var"]
hzar.meta.init(mknBLgM)$varR<-mknBLg$frame["L","var"]
hzar.meta.fix(mknBLgM)$varL <- TRUE
hzar.meta.fix(mknBLgM)$varR <- TRUE

## compile using this method:
mknBLgFR <- hzar.first.fitRequest.gC(gModel=mknBLgM, obsData=mknBLg)
hzar.plot.cline(mknBLgFR)

data(manakinMorphological);
data(manakinLocations);
bcD=manakinLocations[manakinMorphological$Locality,
                     "distance"]
bcV=manakinMorphological$belly.color
bcV=bcV[!is.na(bcD)];bcD=bcD[!is.na(bcD)];
bcD=bcD[!is.na(bcV)];bcV=bcV[!is.na(bcV)];
mknBCclt <-
  hzar.doCLTData1DRaw( distance=bcD,traitValue=bcV)
## Not run: 
hzar.plot.obsData(mknBCclt)

## End(Not run)
mknBCcltM <-
  hzar.makeCline1DCLT(mknBCclt, scaling="free", tails="none");