Gapfill_nls | R Documentation |
This function automatically gap-fills the missing data points (marked as "NA") in the soil respiration dataset using the non-linear Levenberg-Marquardt algorithm as a function of the soil temperature. A Lloyd-Taylor model is used to formulate the relationship (Lloyd & Taylor, 1994). In cases when Lloyd-Taylor model yields large residuals, a basic exponential function is used instead ("Flux~a*exp(b*Ts)").
Gapfill_nls( data, Flux = "Flux", Ts = "Ts", win = 5, interval = 10, R10 = 10, E0 = 400, fail = "ave" )
data |
a data frame that includes the flux (with NA indicating the missing data) and soil temperature |
Flux |
a string indicates the column name for the flux variable to be gap-filled |
Ts |
a string indicates the column name for the soil temperature |
win |
a number indicates the required sampling window length around each gap (total number in two sides), unit: days (default: 5) |
interval |
a number indicates the temporal resolution of the measurements in the dataset, unit: minutes (default: 10) |
R10 |
the start value for the parameter R10 in the Lloyd-Taylor model (default: 10) |
E0 |
the start value for the parameter E0 in the Lloyd-Taylor model (default: 400) |
fail |
a string or a number, what to do when model fails to converge: 1. use the mean value in the sampling window to fill the gap ("ave", default), or 2. use any value assigned here to fill the gap (e.g., 9999, NA, etc.) |
A data frame that includes the original data, gap-filled data ("filled") and a "mark" column that indicates the value in each row of the "filled" is either: 0. original, 1. gap-filled, or 2. failed to converge
Lloyd J., Taylor, J.A., 1994. On the Temperature Dependence of Soil Respiration. Functional Ecology. 8, 315-323.
# read example data df <- read.csv(file = system.file("extdata", "Soil_resp_example.csv", package = "FluxGapsR"),header = T) df_filled <- Gapfill_nls(data = df) # visualize the gapfilled results plot(df_filled$filled,col="red") points(df_filled$Flux)
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