Datasets for "Meteorological factors associated with the timing and abundance of Hymenoscyphus fraxineus spore release" by Burns, Timmermann and Yearsley.

<p>======++++++++++++++++++++++++++++++==============<br> <br> # Data Files:<br> <br> File: burns_etal_preprocessed_data.Rdata<br> <br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This file contains the pre-processed spore count data and the cleaned meteorological data<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The file contains:<br> <br> stations&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The longitude and latitude of the two weather stations used for the metro data<br> varStr_mean&nbsp;&nbsp;&nbsp; Names of the meteorological variables<br> windowStr&nbsp; &nbsp; &nbsp; &nbsp; Names of the three time windows<br> <br> emission&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The main data frame containing the spore and meteorological data<br> &nbsp;&nbsp;&nbsp;&nbsp; date&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Date of a spore count recording. (POSIXlt)<br> &nbsp;&nbsp;&nbsp;&nbsp; year&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Year of spore count recording<br> &nbsp;&nbsp;&nbsp;&nbsp; month&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Month of spore count recording&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp; day&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Day of year of spore count recording<br> &nbsp;&nbsp;&nbsp;&nbsp; total&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The total daily spore count<br> &nbsp;&nbsp;&nbsp;&nbsp; peak&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;The maximum spore count each day&nbsp;&nbsp;&nbsp;&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp; peak_time&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The time (hours after midnight) of the maximum spore count each day<br> &nbsp;&nbsp;&nbsp;&nbsp; peak_time_raw&nbsp;&nbsp;&nbsp; Raw value for time of maximum spore count each day<br> &nbsp;&nbsp;&nbsp;&nbsp; peak_time_date&nbsp;&nbsp; Date and time (POSIXct) for maximum spore count each day<br> ===================================================<br> <br> File: results_burns_etal_daily_emission_analysis_2010_2011_prop0.8.Rdata<br> <br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This file gives the results for the total daily emission of spores<br> <br> File: results_burns_etal_daily_peaktime_analysis_2010_2011_prop0.8.Rdata<br> <br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This file gives the results for the time of the daily per in spore counts<br> <br> ================<br> Both files have the same variables, which are listed below.<br> <br> # Setup parameters<br> use.prop&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Proportion of the data to use for fitting model<br> colinear_threshold&nbsp; The correlation threshold to identify collinear covariates<br> frost_var&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;The name of the variable to use as a frost covariate (three possible windows)<br> k.use&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The dimension of the basis for the smoothing thin-plate splines in the GAM<br> nIter&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Number of Monte-Carlo random subsamples of the data<br> seed&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;The random number seed at the start of the analysis<br> years&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The years of data to use for fitting the GAM models.<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Leaving a year out allows it to be used as independent validation data<br> <br> # Outputs from the analysis<br> var.use&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The names of covariate used in the final analysis after removing collinear covariates<br> models&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;A list (of length nIter) giving all the fitted models<br> d&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; A data frame with a summary of the nIter model results.<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; There are nIter rows. Each row summarises the results from one GAM<br> &nbsp;&nbsp;&nbsp; The data frame contains:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; r2&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; r-squared between the model and the validation data.<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Validation data are the (1-use.prop) proportion not used for fitting<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; r2_fitted.&nbsp; &nbsp; &nbsp;r-squared for the data used to fit the model<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; dev.exp.&nbsp; &nbsp; &nbsp; The explained deviance from the fitted GAM<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; nTerm.&nbsp; &nbsp; &nbsp; &nbsp; The number of smooth terms in the fitted GAM<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; term1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The smooth term with the smallest p-value (number is an index for var.use)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; term2&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The smooth term with the second smallest p-value (number is an index for var.use)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; term3&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The smooth term with the third smallest p-value (number is an index for var.use)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; termF&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The smooth term with the largest F-value (number is an index for var.use)<br> pValues&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;p values for each of the smooth terms (columns) for each of the nIter models (rows)<br> FValues&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;F values for each of the smooth terms (columns) for each of the nIter models (rows)<br> edf&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Estimated degrees of freedom for each of the smooth terms (columns) for each of the nIter models (rows)<br> pValue_param&nbsp;&nbsp;&nbsp;p values for each of the parametric terms (columns) in each of nIter models (rows)<br> tVal_param.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;t statistics for each of the parametric terms (columns) in each of nIter models (rows)<br> &nbsp;</p>