% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/relativehumidity.R
\docType{data}
\name{RelativeHumidity}
\alias{RelativeHumidity}
\title{Monthly Relative Humidity Data}
\format{
A data frame with 312 observations and 11 variables:
\describe{
  \item{date}{Observation date (YYYY-MM-DD)}
  \item{rh}{Monthly mean relative humidity, originally measured in percent and
  rescaled to the unit interval (0,1)}
  \item{ins}{Monthly total insolation (in hours), contains 2 missing values}
  \item{ins2}{Monthly total insolation (in hours) with missing values imputed
  via seasonal interpolation}
  \item{pre}{Monthly total precipitation (in mm), contains 2 missing values}
  \item{pre2}{Monthly total precipitation (in mm) with missing values imputed
  via seasonal interpolation}
  \item{neb}{Monthly mean cloudiness (in tenths)}
  \item{ap}{Monthly mean atmospheric pressure (in hPa)}
  \item{mt}{Monthly mean temperature (in Degrees Celsius)}
  \item{ws}{Monthly mean wind speed (in m/s)}
  \item{dir}{Monthly predominant wind direction (in degrees)}
}
}
\source{
Brazilian meteorological station
}
\usage{
data(RelativeHumidity)
}
\description{
Monthly meteorological data including relative humidity (rh),
temperature, insolation, precipitation, and wind speed for a
Brazilian station (2000-2025).

The dataset contains two missing observations in the variables \code{ins}
and \code{pre}, corresponding to September 2020 and November 2025. To address
these missing values, imputation was performed via seasonal interpolation using
the \pkg{imputeTS} package, with the imputed versions stored as \code{ins2}
and \code{pre2}.
}
\examples{
# Load the dataset
data(RelativeHumidity)

# View first rows
head(RelativeHumidity)

# Check structure
str(RelativeHumidity)

# Insolation with and without imputation
plot(RelativeHumidity$ins, type = "l", col = "red",
     ylab = "Insolation", main = "Missing values visible as gaps")
points(RelativeHumidity$ins2, type = "l", col = "blue")
}
\keyword{datasets}
