index.periodic: Estimate indices in periodic timeseries based on anchored...

In HelpersMG: Tools for Environmental Analyses, Ecotoxicology and Various R Functions

Estimate indices in periodic timeseries based on anchored minimum and maximum

Description

Estimate indices in periodic timeseries based on anchored minimum and maximum.
The data.frame minmax can be generated manually. It should have three columns (time, index, SD), with all the successive minimum and maximum indices.
It can be used with sun.info() to get the time of minimum and maximum air temperature or with getTide() to reconstruct the sea level.

Usage

index.periodic(minmax, time = NULL, replicates = 100, progressbar = FALSE)

Arguments

minmax	A data.frame returned by minmax.periodic
time	The time at which produced the estimate
replicates	Number of replicates to estimate SD
progressbar	Does a progression bar must be shown

Details

index.periodic estimate indices in periodic timeseries based on anchored minimum and maximum

Value

A data.frame with a column time and a column index

Author(s)

Marc Girondot [e-mail]

See Also

Other Periodic patterns of indices: minmax.periodic(), moon.info(), sun.info(), tide.info()

Examples

## Not run: 
# Generate a timeserie of time
time.obs <- NULL
for (i in 0:9) time.obs <- c(time.obs, c(0, 6, 12, 18)+i*24)
# For these time, generate a timeseries of temperatures
temp.obs <- rep(NA, length(time.obs))
temp.obs[3+(0:9)*4] <- rnorm(10, 25, 3)
temp.obs[1+(0:9)*4] <- rnorm(10, 10, 3)
for (i in 1:(length(time.obs)-1)) 
  if (is.na(temp.obs[i])) 
  temp.obs[i] <- mean(c(temp.obs[i-1], temp.obs[i+1]))
  if (is.na(temp.obs[length(time.obs)])) 
  temp.obs[length(time.obs)] <- temp.obs[length(time.obs)-1]/2
observed <- data.frame(time=time.obs, temperature=temp.obs)
# Search for the minimum and maximum values
r <- minmax.periodic(time.minmax.daily=c(Min=2, Max=15), 
observed=observed, period=24, colname.index="temperature")

# Estimate all the temperatures for these values
t <- index.periodic(minmax=r)

plot_errbar(x=t[,"time"], y=t[,"index"],
errbar.y=ifelse(is.na(t[,"sd"]), 0, 2*t[,"sd"]),
type="l", las=1, bty="n", errbar.y.polygon = TRUE, 
xlab="hours", ylab="Temperatures", ylim=c(0, 35), 
errbar.y.polygon.list = list(col="grey"))

plot_add(x=t[,"time"], y=t[,"index"], type="l")

plot_add(observed$time, observed$temperature, pch=19, cex=0.5)

## End(Not run)

HelpersMG documentation built on Oct. 5, 2023, 5:08 p.m.