new_matrixfit: perform a factorising fit of a matrix of correlation...

Description Usage Arguments Details Value

View source: R/new_matrixfit.R

Description

Modernised and extended implementation of matrixfit

Usage

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new_matrixfit(cf, t1, t2, parlist, sym.vec = rep(1, cf$nrObs),
  neg.vec = rep("cosh", cf$nrObs), useCov = FALSE, model = "single",
  boot.fit = TRUE, fit.method = "optim", autoproceed = FALSE, par.guess,
  every, higher_states = list(val = numeric(0), boot = matrix(nrow = 0, ncol
  = 0), ampl = numeric(0)), ...)

Arguments

cf

Object of class cf with cf_meta and cf_boot.

t1

Integer, start time slice of fit range (inclusive).

t2

Integer, end time slie of fit range (inclusive).

parlist

Numeric vector, list of parameters for the model function.

sym.vec

Integer, numeric or vectors thereof specifying the symmetry properties of the correlation functions stored in cf. See matrixfit for details.

neg.vec

Integer or integer vector of global signs, see matrixfit for details.

useCov

Boolean, specifies whether a correlated chi^2 fit should be performed.

model

String, specifies the type of model to be assumed for the correlator. See below for details.

boot.fit

Boolean, specifies if the fit should be bootstrapped.

fit.method

String, specifies which minimizer should be used. See matrixfit for details.

autoproceed

Boolean, if TRUE, specifies that if inversion of the covariance matrix fails, the function should proceed anyway assuming no correlation (diagonal covariance matrix).

par.guess

Numeric vector, initial values for the paramters, should be of the same length as parlist.

every

Integer, specifies a stride length by which the fit range should be sparsened, using just everyth time slice in the fit.

higher_states

List with elements val and boot. Only used in the n_particles fit model. The member val must have the central energy values for all the states that are to be fitted. The boot member will be a matrix that has the various states as columns and the corresponding bootstrap samples as rows. The length of val must be the column number of boot. The row number of boot must be the number of samples.

...

Further parameters.

Details

There are different fit models available. The models generally depend on one or multiple energies E and amplitudes p_i which for a general matrix are row- and column-amplitudes. The relative sign factor c \in \{-1, 0, +1\} depends on the chosen symmetry of the correlator. It is a plus for a “cosh” symmetry and a minus for a “sinh” symmetry. If the back propagating part is to be neglected (just “exp” model), it will be zero.

When the back propagating part is not taken into account, then the single, shifted and weighted model become the same except for changes in the amplitude.

Value

See bootstrap.nlsfit.


hadron documentation built on Jan. 13, 2021, 8 a.m.