View source: R/rcspline.restate.s

rcspline.restate | R Documentation |

This function re-states a restricted cubic spline function in
the un-linearly-restricted form. Coefficients for that form are
returned, along with an **R** functional representation of this function
and a LaTeX character representation of the function.
`rcsplineFunction`

is a fast function that creates a function to
compute a restricted cubic spline function with given coefficients and
knots, without reformatting the function to be pretty (i.e., into
unrestricted form).

```
rcspline.restate(knots, coef,
type=c("ordinary","integral"),
x="X", lx=nchar(x),
norm=2, columns=65, before="& &", after="\\",
begin="", nbegin=0, digits=max(8, .Options$digits))
rcsplineFunction(knots, coef, norm=2, type=c('ordinary', 'integral'))
```

`knots` |
vector of knots used in the regression fit |

`coef` |
vector of coefficients from the fit. If the length of |

`type` |
The default is to represent the cubic spline function corresponding
to the coefficients and knots. Set |

`x` |
a character string to use as the variable name in the LaTeX expression for the formula. |

`lx` |
length of |

`norm` |
normalization that was used in deriving the original nonlinear terms
used in the fit. See |

`columns` |
maximum number of symbols in the LaTeX expression to allow before inserting a newline (‘\\’) command. Set to a very large number to keep text all on one line. |

`before` |
text to place before each line of LaTeX output. Use ‘"& &"’ for an equation array environment in LaTeX where you want to have a left-hand prefix e.g. ‘"f(X) & = &"’ or using ‘"\lefteqn"’. |

`after` |
text to place at the end of each line of output. |

`begin` |
text with which to start the first line of output. Useful when adding LaTeX output to part of an existing formula |

`nbegin` |
number of columns of printable text in |

`digits` |
number of significant digits to write for coefficients and knots |

`rcspline.restate`

returns a vector of coefficients. The
coefficients are un-normalized and two coefficients are added that are
linearly dependent on the other coefficients and knots. The vector of
coefficients has four attributes. `knots`

is a vector of knots,
`latex`

is a vector of text strings with the LaTeX
representation of the formula. `columns.used`

is the number of
columns used in the output string since the last newline command.
`function`

is an **R** function, which is also return in character
string format as the `text`

attribute. `rcsplineFunction`

returns an **R** function with arguments `x`

(a user-supplied
numeric vector at which to evaluate the function), and some
automatically-supplied other arguments.

Frank Harrell

Department of Biostatistics, Vanderbilt University

fh@fharrell.com

`rcspline.eval`

, `ns`

, `rcs`

,
`latex`

, `Function.transcan`

```
set.seed(1)
x <- 1:100
y <- (x - 50)^2 + rnorm(100, 0, 50)
plot(x, y)
xx <- rcspline.eval(x, inclx=TRUE, nk=4)
knots <- attr(xx, "knots")
coef <- lsfit(xx, y)$coef
options(digits=4)
# rcspline.restate must ignore intercept
w <- rcspline.restate(knots, coef[-1], x="{\\rm BP}")
# could also have used coef instead of coef[-1], to include intercept
cat(attr(w,"latex"), sep="\n")
xtrans <- eval(attr(w, "function"))
# This is an S function of a single argument
lines(x, coef[1] + xtrans(x), type="l")
# Plots fitted transformation
xtrans <- rcsplineFunction(knots, coef)
xtrans
lines(x, xtrans(x), col='blue')
#x <- blood.pressure
xx.simple <- cbind(x, pmax(x-knots[1],0)^3, pmax(x-knots[2],0)^3,
pmax(x-knots[3],0)^3, pmax(x-knots[4],0)^3)
pred.value <- coef[1] + xx.simple %*% w
plot(x, pred.value, type='l') # same as above
```

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