B0_sma | R Documentation |
It calculates the intercept (B0) for the bivariate linear relationship between predicted and observed values following the SMA regression.
B0_sma(data = NULL, obs, pred, orientation = "PO", tidy = FALSE, na.rm = TRUE)
data |
(Optional) argument to call an existing data frame containing the data. |
obs |
Vector with observed values (numeric). |
pred |
Vector with predicted values (numeric). |
orientation |
Argument of class |
tidy |
Logical operator (TRUE/FALSE) to decide the type of return. TRUE returns a data.frame, FALSE returns a list; Default : FALSE. |
na.rm |
Logic argument to remove rows with missing values (NA). Default is na_rm = TRUE. |
SMA is a symmetric linear regression (invariant results/interpretation to axis orientation) recommended to describe the bivariate scatter instead of OLS regression (classic linear model, which results vary with the axis orientation). For the formula and more details, see online-documentation
an object of class numeric
within a list
(if tidy = FALSE) or within a
data frame
(if tidy = TRUE).
Warton et al. (2006). Bivariate line-fitting methods for allometry. Biol. Rev. Camb. Philos. Soc. 81, 259–291. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/1521-4036(200203)44:2<161::AID-BIMJ161>3.0.CO;2-N")}
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
B0_sma(obs = X, pred = Y)
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