polyStatsLevel2AM(level2AM, func, id=NULL)

# Specifying the path to GEDI level2A data (zip file)
outdir = tempdir()
level2A_fp_zip <- system.file("extdata",
                  "GEDI02_A_2019108080338_O01964_T05337_02_001_01_sub.zip",
                  package="rGEDI")

# Unzipping GEDI level2A data
level2Apath <- unzip(level2A_fp_zip,exdir = outdir)

# Reading GEDI level2A data (h5 file)
level2a<-readLevel2A(level2Apath=level2Apath)

# Specifying the path to shapefile
polygon_filepath <- system.file("extdata", "stands_cerrado.shp", package="rGEDI")

# Reading shapefile as SpatialPolygonsDataFrame object
library(raster)
polygon_spdf<-shapefile(polygon_filepath)

# Extracting GEDI Eleveation and Relative Metrics (level2A)
level2AM<-getLevel2AM(level2a)
head(level2AM)

# Clipping GEDI data by geometry
level2AM_clip = clipLevel2AMGeometry(level2AM, polygon_spdf, split_by="id")

#' Define your own function
mySetOfMetrics = function(x)
{
metrics = list(
   min =min(x), # Min of x
   max = max(x), # Max of x
   mean = mean(x), # Mean of x
   sd = sd(x)# Sd of x
 )
 return(metrics)
}

# Computing the maximum of RH100
RH100max<-polyStatsLevel2AM(level2AM_clip,func=max(rh100), id=NULL)

# Computing the maximum of RH100 stratified by polygon
RH100max_poly<-polyStatsLevel2AM(level2AM_clip,func=max(rh100), id=NULL)

# Computing a serie statistics for GEDI metrics stratified by polygon
RH100metrics<-polyStatsLevel2AM(level2AM_clip,func=mySetOfMetrics(rh100),
                     id=level2AM_clip$id)

close(level2a)