R: Model REE + Y contents using different methods.

model_REE {imputeREE}

R Documentation

Model REE + Y contents using different methods.

Description

This function models REE + Y using different methods. The Chondrite-Lattice method use a linear regression between the REE (+Y) chondrite-normalized and the missfit term from the lattice strain equation (ri/3 + r0/6)(ri-r0)^2. The Chondrite-Onuma method use the quadratic relationship between the ionic radii and chondrite normalized REE values. The method of Zhong et al. (2019) use a logaritmic relationship between the atomic number of the REE and the chondrite normalized REE. For details in the lattice strain theory, see Blundy and Wood 1994. For more details in the imputation methods see Carrasco-Godoy and Campbell (2023), and Zhong et al. (2019)

Usage

model_REE(
  dat,
  method = 1,
  long_format = F,
  exclude = c("La", "Pr", "Ce", "Eu", "Y"),
  r0 = 0.84,
  chondrite = PalmeOneill2014CI,
  estimate_r0 = FALSE,
  r0_step = 0.01,
  r0_min = 0.01,
  r0_max = 0.15,
  prefix = NULL,
  suffix = NULL,
  Calibrate = T,
  Pr_correction_fact = 1/0.918,
  Y_correction_fact = 1/0.72,
  Dy_correction_fact = 1/1.032,
  Ho_correction_fact = 1,
  Er_correction_fact = 1/0.974,
  Tm_correction_fact = 1,
  Yb_correction_fact = 1/0.8785,
  Lu_correction_fact = 1/0.8943,
  Nd_correction_fact = 1/0.989,
  Sm_correction_fact = 1/1.022,
  Gd_correction_fact = 1/1.033,
  Tb_correction_fact = 1/1.05
)

Arguments

`dat`	A data frame with REE data in ppm
`method`	a number. a choice of `1` for Chondrite Lattice or `2` for Zhong et al. (2019) or `3` for Chondrite-Onuma method.
`long_format`	If T, rectangular long data is returned.
`exclude`	a string: vector including elements that should be omitted from modelling. La, Ce and Eu are the default. Ce and Eu should be always included
`r0`	A number: ionic radii of the lattice site r0. By default is 0.87 A, the median value obtained by Carrasco-Godoy and Campbell.
`chondrite`	an option from: PalmeOneill2014CI, Oneill2014Mantle, McDonough1995CI
`estimate_r0`	If T, r0 is estimated using a method similar to the one from Loader et al. 2022.
`r0_step`	If r0 is estimated, this define the step for iteration. smaller step heavily increases the computing time.
`r0_min`	Minimun value from which the iteration starts. Calculated from r0.
`r0_max`	Maximun value at which iteration ends. Calculated from r0.
`prefix`	A prefix in your columns e.g. ICP_La
`suffix`	A suffix in your columns e.g. La_ppm
`Calibrate`	Logical (T or F). If True, the model is calibrated using the correction factors. By default it is the reciprocal of the median REE from the work of Carrasco-Godoy and Campbell is used.
`Pr_correction_fact`	a number: correction factor for overestimated Pr 1/0.918
`Y_correction_fact`	a number: correction factor for underestimated Y. 1/ 0.72 by default.
`Dy_correction_fact`	a number: correction factor for overestimated Dy 1/1.032
`Ho_correction_fact`	a number: correction factor for Ho. 1 by default.
`Er_correction_fact`	a number: correction factor for underestimated Er. 1/0.97 by default.
`Tm_correction_fact`	a number: correction factor for Tm. 1 by default.
`Yb_correction_fact`	a number: correction factor for underestimated Yb. 1/0.8785 by default.
`Lu_correction_fact`	a number: correction factor for underestimated Lu. 1/0.8943 by default.
`Nd_correction_fact`	a number: correction factor for underestimated Nd 1/0.0.989
`Sm_correction_fact`	a number: correction factor for overestimated Sm 1/1.022
`Gd_correction_fact`	a number: correction factor for overestimated Gd 1/1.033
`Tb_correction_fact`	a number: correction factor for overestimated Tb 1/1.050

Value

a dataframe

Examples


Ballard_et_al_Zircon %>%  model_REE(prefix = 'Zr', suffix = 'ppm')