york_fit | R Documentation |
york_fit()
calculates the regression parameters of
an error-considering linear regression.
york_fit(x, y, x_err, y_err, r = 0)
x |
vector of x values. |
y |
vector of y values. Has to be same the length as x. |
x_err |
Error on the x values. Has to be same the length as x. |
y_err |
Error on the y values. Has to be same the length as x. |
r |
Correlation coefficient of x_err and y_err at each data point.
Default: |
Regression fitting method according to York et al. (2004). The algorithm is described in the appendix of Wacker et al. (2014).
A list with regression parameters:
slope and its standard error
intercept and its standard error
weights of the points (normalized to 1)
residual standard error (sigma)
R2
p-value (two-tailed t-test).
Julian Tödter
York, D., Evensen, N. M., López Martínez, M., & De Basabe Delgado, J. (2004). Unified equations for the slope, intercept, and standard errors of the best straight line. American Journal of Physics, 72(3), 367-375. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1119/1.1632486")}
Wacker, U., Fiebig, J., Tödter, J., Schöne, B. R., Bahr, A., Friedrich, O., et al. (2014). Empirical calibration of the clumped isotope paleothermometer using calcites of various origins. Geochimica et Cosmochimica Acta, 141, 127-144. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.gca.2014.06.004")}
york_fit(
x = c(1, 2, 3),
y = c(1.1, 1.9, 3.2),
x_err = c(0.1, 0.2, 0.1),
y_err = c(0.2, 0.1, 0.2))
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