Generate series-level descriptive statistics for fhx object
series_stats(
x,
func_list = list(first = first_year, last = last_year, years = count_year_span,
inner_type = inner_type, outer_type = outer_type, number_scars = count_scar,
number_injuries = count_injury, recording_years = count_recording, mean_interval =
series_mean_interval)
)An fhx object.
A list of named functions that will be run on each series
in the fhx object. The list name for each function is the corresponding
column name in the output data frame.
A data.frame containing series-level statistics.
fhx() creates an fhx object.
as_fhx() casts data frame into an fhx object.
first_year() gets earliest year in an fhx object.
last_year() gets latest year in an fhx object.
count_year_span() counts the year span of an fhx object.
inner_type() gets "rec_type" for inner event of an fhx object.
outer_type() get "rec_type" for outside event of an fhx object.
count_scar() counts scars in an fhx object.
count_injury() counts injuries in an fhx object.
count_recording() counts recording years in fhx object.
series_mean_interval() quickly estimates mean fire-interval of fhx
object.
sample_depth() gets sample depth of an fhx object.
summary.fhx() brief summary of an fhx object.
composite() create a fire composite from an fhx object.
intervals() get fire intervals analysis from composite.
sea() superposed epoch analysis.
data(lgr2)
series_stats(lgr2)
#> series first last years inner_type outer_type number_scars number_injuries
#> 1 LGR54 1366 1482 117 inner_year outer_year 0 1
#> 2 LGR44 1411 1503 93 inner_year outer_year 2 0
#> 3 LGR47 1580 1770 191 pith_year outer_year 0 0
#> 4 LGR48 1701 1804 104 pith_year outer_year 0 1
#> 5 LGR46 1705 1849 145 pith_year outer_year 3 0
#> 6 LGR41 1721 1853 133 pith_year outer_year 0 1
#> 7 LGR52 1758 1837 80 pith_year outer_year 1 1
#> 8 LGR51 1759 1851 93 pith_year bark_year 0 0
#> 9 LGR45 1760 1811 52 inner_year outer_year 0 1
#> 10 LGR49 1766 1826 61 pith_year outer_year 1 0
#> 11 LGR53 1772 1843 72 pith_year outer_year 1 0
#> 12 LGR43 1777 1860 84 inner_year bark_year 1 0
#> 13 LGR55 1801 2012 212 inner_year bark_year 0 1
#> 14 LGR56 1861 2011 151 pith_year bark_year 0 0
#> 15 LGR36 1865 2011 147 pith_year bark_year 0 0
#> 16 LGR33 1867 2011 145 pith_year bark_year 0 0
#> 17 LGR31 1868 2011 144 pith_year bark_year 0 0
#> 18 LGR32 1868 2011 144 pith_year bark_year 0 0
#> 19 LGR27 1869 2011 143 pith_year bark_year 0 0
#> 20 LGR29 1875 2012 138 pith_year bark_year 0 0
#> 21 LGR25 1876 2011 136 inner_year bark_year 0 0
#> 22 LGR35 1877 2011 135 pith_year bark_year 0 0
#> 23 LGR30 1878 2011 134 pith_year bark_year 0 0
#> 24 LGR26 1884 2011 128 pith_year bark_year 0 0
#> 25 LGR42 1894 1970 77 pith_year outer_year 0 0
#> 26 LGR34 1904 2011 108 inner_year bark_year 0 0
#> recording_years mean_interval
#> 1 60 NA
#> 2 81 25.0
#> 3 191 NA
#> 4 53 NA
#> 5 77 16.5
#> 6 48 NA
#> 7 65 NA
#> 8 93 NA
#> 9 6 NA
#> 10 21 NA
#> 11 38 NA
#> 12 55 NA
#> 13 152 NA
#> 14 151 NA
#> 15 147 NA
#> 16 145 NA
#> 17 144 NA
#> 18 144 NA
#> 19 143 NA
#> 20 138 NA
#> 21 136 NA
#> 22 135 NA
#> 23 134 NA
#> 24 128 NA
#> 25 77 NA
#> 26 108 NA
# You can create your own list of statistics to output. You can also create
# your own functions:
flist <- list(
n = count_year_span,
xbar_interval = function(x) mean_interval(x, injury_event = TRUE)
)
sstats <- series_stats(lgr2)
head(sstats)
#> series first last years inner_type outer_type number_scars number_injuries
#> 1 LGR54 1366 1482 117 inner_year outer_year 0 1
#> 2 LGR44 1411 1503 93 inner_year outer_year 2 0
#> 3 LGR47 1580 1770 191 pith_year outer_year 0 0
#> 4 LGR48 1701 1804 104 pith_year outer_year 0 1
#> 5 LGR46 1705 1849 145 pith_year outer_year 3 0
#> 6 LGR41 1721 1853 133 pith_year outer_year 0 1
#> recording_years mean_interval
#> 1 60 NA
#> 2 81 25.0
#> 3 191 NA
#> 4 53 NA
#> 5 77 16.5
#> 6 48 NA