`sim2ddata`

simulates kinetic data for the sequential reaction
A -> B -> C with the time constants k1 and k2.

1 2 3 |

`L` |
Positive, non-zero integer specifying how many spectral variables should be used to describe the kinetic dataset. |

`t` |
Numeric vector containing non-negative real numbers describing at which reaction times the kinetic data should be sampled. |

`k1, k2` |
Positive, non-zero real numbers describing the time constants
used to simulate the reactions A -> B ( |

`X` |
Numeric vector with two values specifying the range of the simulated spectral variables. |

`A, B, C` |
Numeric vector with two real values specifying the two signal
positions of species A, B and C, respectively. It's the |

`Aamp, Bamp, Camp` |
Numeric vector with two values specifying the signal
width of species A, B and C, respectively. It's the standard deviation
( |

The simulation assumes 2 spectral signals for each of the 3 species A, B and C. The sequential reaction is defined by 2 time constants k1 and k2. The spectral information can be sampled at every point during the reaction to get an arbitrary profile of the kinetic data. The signals of the three species are modeled by a normal distribution. In addition the spectral variable is assumed to be equidistant and the number of spectral variables can also be chosen arbitrary.

`sim2ddata`

returns a matrix containing the kinetic data. The
matrix contains the sampled reaction times by rows and the spectral
variables by columns. The reaction times are the row names while the
spectral variables are saved as the column names. The matrix has the
ideal format to be analyzed by `corr2d`

.

The default values are inspired by: I. Noda (2014) <DOI:10.1016/j.molstruc.2014.01.024>

1 2 3 4 5 | ```
testdata <- sim2ddata()
twodtest <- corr2d(testdata, corenumber = 1)
plot_corr2d(twodtest)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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