Calculate maximal mean values for specified time periods.

1 |

`data` |
a |

`column` |
column in |

`windows` |
window size(s) for which to generate best averages, given in seconds. |

`deltat` |
the sampling frequency of |

`character.only` |
are column name arguments given as character strings? A backdoor around non-standard evaluation. Mainly for internal use. |

a matrix object with two rows: 1) best mean values and 2) the time at which those values were recorded

For a more generic and efficient version of this function, see
`mmv2`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(ridedata)
## Best power for 5 and 20 minutes.
tsec <- c(5, 20) * 60
mmv(ridedata, power.W, tsec)
## Generate a simple critical power estimate.
tsec <- 2:20 * 60
pwrs <- mmv(ridedata, power.W, tsec)
m <- lm(pwrs[1, ] ~ {1 / tsec}) # Simple inverse model.
coef(m)[1] # Intercept = critical power.
## More complex models...
m <- Pt_model(pwrs[1, ], tsec)
print(m)
## Extract the asymptote of the exponential model.
coef(m)$exp["CP"]
``` |

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