logger$info("Entering trend analysis section")
For each location code and the type names and group codes specified in the settings file, the following statistics have been estimated for the period r str_c(DATE_FROM, " to ", DATE_TO)
:
A p-value less than an a priori specified significance level (e.g., often α = 0.05), indicates a significant trend. If the p-value is greater than this significance level, we can't say that there is no trend. We can only conclude that our data do not show evidence for a significant trend (due to lack of data, noise, etc.).
The Mann-Kendall test is a non-parametric test and as such does not make distributional assumptions on the data.
# check location_codes missing_location_codes <- LOCATION_CODE %>% setdiff(unique(d_stats$location_code)) if (length(missing_location_codes) > 0) { logger$warn("The following specified location code(s) are not found and will be skipped: ", missing_location_codes %>% sQuote %>% enumerate) } LOCATION_CODE <- d_stats %>% chuck("location_code") %>% unique %>% intersect(LOCATION_CODE) # check type names missing_type_names <- TYPE_NAME %>% setdiff(unique(d_stats$type_name)) if (length(missing_type_names) > 0) { logger$warn("The following specified type name(s) are not found and will be skipped: ", missing_type_names %>% sQuote %>% enumerate) } TYPE_NAME <- d_stats %>% chuck("type_name") %>% unique %>% intersect(TYPE_NAME) # check group codes missing_group_codes <- GROUP_CODE %>% setdiff(unique(d_stats$type_name)) if (length(missing_group_codes) > 0) { logger$warn("The following specified group code(s) are not found and will be skipped: ", missing_group_codes %>% sQuote %>% enumerate) } GROUP_CODE <- d_stats %>% chuck("type_name") %>% unique %>% intersect(GROUP_CODE)
logger$info("Creating table with trend statistics") d_stats %>% filter(type_name %in% unique(c("TC", TYPE_NAME, GROUP_CODE))) %>% mutate( p_value = formatC(p_value, format = "f", digits = 4), slope = b1 * 365.25) %>% select(location_code, type_name, from, to, N = n, slope, `p-value` = p_value) %>% arrange(location_code, desc(abs(slope))) %>% rename(`type name / group code` = type_name) %>% mutate_if( is_double, formatC, format = "fg", digits = 4) %>% kable(align = "llllrrr") logger$info("Table with trend statistics created")
Descriptive statisics and trend analysis results have been stored in file
r sQuote(basename(FILE_STATS))
.
logger$info("No valid location_code(s) found. Therefore, time-series plot are skipped.")
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