lmr_data | R Documentation |
lm
Simple Linear RegressionComputes an lm
object for a simple linear regression from a range of x
and y
values,
including intermediate values. If r
is not given then zero correlation is used (with cor_data
).
digits
determines the rounding for the x
and y
values. If only one value is given, then
it will be used for x
and y
. If no value is given then it will be determined from
the x
and y
values by 3+ceiling(-log10(diff(range(.))))
.
lmr_data(xr, yr, n, r = 0, digits = NULL, ...)
lm_regression_data(xr, yr, n, r = 0, digits = NULL, ...)
xr |
numeric: range of x values |
yr |
numeric: range of y values |
n |
numeric: number of observations to generate |
r |
numeric: desired correlation, uses |
digits |
numeric(2): digits for rounding, for x |
... |
further parameters used in |
An object of the class lm
with the additional components:
x
the generated x values
y
the generated y values
sumx
\sum_{i=1}^n x_i
sumy
\sum_{i=1}^n y_i
sumx2
\sum_{i=1}^n x_i^2
sumy2
\sum_{i=1}^n y_i^2
sumxy
\sum_{i=1}^n x_i y_i
meanx
the mean of x: 1/n \sum_{i=1}^n x_i
meany
the mean of y: 1/n \sum_{i=1}^n y_i
varx
the variation of x: \sum_{i=1}^n (x_i-\bar{x})^2
vary
the variation of y: \sum_{i=1}^n (y_i-\bar{y})^2
varxy
the common variation of x and y:\sum_{i=1}^n (x_i-\bar{x})(y_i-\bar{y})
sxy
the covariance of x and y
rxy
the correlation of x and y
b0
the intercept of the linear regression
b1
the slope of the linear regression
r2
the coefficient of determination of the linear regression
# Engine displacement typically ranges from 500 to 2000 cm^3
# Fuel economy typically ranges from 2 to 8 liter/100 km
lmr <- lmr_data(c(500, 2000), c(2, 8), n=8)
str(lmr)
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