Return a data frame, matrix or vector which linearly interpolates data from a given matrix or data frame.

1 2 3 4 5 6 7 8 9 | ```
approxTime(x, xout, ...)
approxTime1(x, xout, rule = 1)
approxTimeEq(x, xout, ...)
approxTimeEq1(x, xout, rule = 1)
findIndexEq(x, xout, rule = 1)
``` |

`x` |
a matrix or data frame with numerical values giving coordinates of points to be interpolated. The first column needs to be in ascending order and is interpreted as independent variable (e.g. time), the remaining columns are used as dependent variables. |

`xout` |
a vector (or single value for |

`...` |
optional parameters passed to |

`rule` |
an integer describing how interpolation is to take place outside
the interval [min(x), max(x)]. If |

The functions can be used for linear interpolation with a complete matrix or
data frame. This can be used for example in the main function of an
`odeModel`

to get input values at a specified time `xout`

.
Versions `approxTime1`

, `approxTimeEq`

amd `approxTimeEq1`

are less flexible
(only one single value for `xout`

or/and equidistant values of of time in `x`

and only linear interpolation) but have increased performance. All interpolation
functions are faster if `x`

is a matrix instead of a data frame.

`approxTime`

returns a matrix resp. data frame of the same
structure as `x`

containing data which interpolate the given data with
respect to `xout`

. `approxTime1`

is a performance optimized
special version with less options than the original `approx`

function.
It returns an interpolated vector.

`approxfun`

1 2 | ```
inputs <- data.frame(time = 1:10, y1 = rnorm(10), y2 = rnorm(10, mean = 50))
input <- approxTime(inputs, c(2.5, 3), rule = 2)
``` |

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