FourPHFfit.bulk: Fit four-parameter hill function for multiple samples

Description

Fit four-parameter hill function from a data frame of germination counts recorded at specific time intervals for multiple samples in batch.

Usage

FourPHFfit.bulk(
  data,
  total.seeds.col,
  counts.intervals.cols,
  intervals,
  partial = TRUE,
  fix.y0 = TRUE,
  fix.a = TRUE,
  tmax,
  xp = c(10, 60),
  umin = 10,
  umax = 90,
  tries = 3
)

Arguments

data

A data frame with the germination count data. It should possess columns with

Partial or cumulative germination counts per time interval (to be indicated by the argument counts.intervals.cols and
Total number of seeds tested (to be indicated by the argument total.seeds.col).

total.seeds.col

The name of the column in data with the total number of seeds tested.

counts.intervals.cols

The names of columns in data with the germination counts (partial or cumulative, as indicated by the argument partial) per time interval (indicated by the argument intervals).

intervals

The time intervals.

partial

logical. If TRUE, germ.counts is considered as partial and if FALSE, it is considered as cumulative. Default is TRUE.

fix.y0

Force the intercept of the y axis through 0.

fix.a

Fix a as the actual maximum germination percentage at the end of the experiment.

tmax

The time up to which AUC is to be computed.

Germination percentage value(s) for which the corresponding time is to be computed as a numeric vector. Default is c(10, 60).

umin

The minimum germination percentage value for computing uniformity. Default is 10. Seed Details.

umax

The maximum germination percentage value for computing uniformity. Default is 90. Seed Details.

tries

The number of tries to be attempted to fit the curve. Default is 3.

Value

A data frame with the original data along with the various parameters of the respective fitted four-parameter hill function.

References

el-kassaby_seed_2008germinationmetrics

Examples

Run this code

# NOT RUN {
# }
# NOT RUN {
data(gcdata)

counts.per.intervals <- c("Day01", "Day02", "Day03", "Day04", "Day05",
                          "Day06", "Day07", "Day08", "Day09", "Day10",
                          "Day11", "Day12", "Day13", "Day14")

FourPHFfit.bulk(gcdata, total.seeds.col = "Total Seeds",
                    counts.intervals.cols = counts.per.intervals,
                    intervals = 1:14, partial = TRUE,
                    fix.y0 = TRUE, fix.a = TRUE, xp = c(10, 60),
                    tmax = 20, tries = 3, umax = 90, umin = 10)
# }
# NOT RUN {
# }