 Fitting Wave Height Data to a Probability Distribution - Maple Help

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The University of Maine records real-time accelerometer data from buoys deployed in the Gulf of Maine and the Caribbean (http://gyre.umeoce.maine.edu/buoyhome.php). The data can be downloaded from their website, and includes the significant wave height recorded at regular intervals for the last few months.

This application does the following:

 • Downloads accelerometer data for Buoy PR206 (located just off the coast of Puerto Rico at a latitude of 18° 28.46' N and a longitude of 66° 5.94' W)
 • Fits the significant wave height to a Weibull distribution by using two methods: maximum likelihood estimation and moment matching
 • Plots the fitted distributions on top of a histogram of the experimental data

The Google Maps component below gives the location of buoy PR206. Latitude Longitude Zoom Level Map Type roadmapsatelliteterrainhybrid > $\mathrm{restart}:$
 > $\mathrm{with}\left(\mathrm{plots}\right):\mathrm{with}\left(\mathrm{Statistics}\right):\mathrm{with}\left(\mathrm{Optimization}\right):$
 > $\mathrm{url}≔"http://gyre.umeoce.maine.edu/data/gomoos/buoy/php/view_csv_file.php?ncfile=/data/gomoos/buoy/archive/PR206/realtime/PR206.waves.triaxys.realtime.nc":$
 > $\mathrm{data}≔\mathrm{ImportMatrix}\left(\mathrm{url}\right)$
 ${\mathrm{data}}{≔}\left[\begin{array}{c}{\mathrm{8274 x 6}}{\mathrm{Matrix}}\\ {\mathrm{Data Type:}}{\mathrm{anything}}\\ {\mathrm{Storage:}}{\mathrm{rectangular}}\\ {\mathrm{Order:}}{\mathrm{Fortran_order}}\end{array}\right]$ (2.1)
 > $\mathrm{sigWaveHeight}≔\mathrm{RemoveNonNumeric}\left(\mathrm{data}\left[..,2\right]\right):$
 > $\mathrm{n}≔\mathrm{numelems}\left(\mathrm{sigWaveHeight}\right)$
 ${n}{≔}{8273}$ (2.2)
 > $\mathrm{numBins}≔40:$
 > $\mathrm{p1}≔\mathrm{Histogram}\left(\mathrm{sigWaveHeight},\mathrm{bincount}=\mathrm{numBins},\mathrm{color}=\mathrm{COLOR}\left(\mathrm{RGB},\frac{150}{255},\frac{40}{255},\frac{27}{255}\right),\mathrm{thickness}=0,\mathrm{style}=\mathrm{patchnogrid},\mathrm{transparency}=0.5,\mathrm{background}=\mathrm{ColorTools}:-\mathrm{Color}\left("RGB",\left[\frac{236}{255},\frac{240}{255},\frac{241}{255}\right]\right),\mathrm{axis}=\left[\mathrm{gridlines}=\left[10,\mathrm{color}=\mathrm{RGB}\left(1,1,1\right)\right]\right],\mathrm{axesfont}=\left[\mathrm{Arial}\right],\mathrm{labels}=\left["Significant Wave Height \left(m\right)","Distribution"\right],\mathrm{labeldirections}=\left[\mathrm{horizontal},\mathrm{vertical}\right],\mathrm{labelfont}=\left[\mathrm{Arial}\right],\mathrm{size}=\left[800,500\right]\right):$
 > $\mathrm{display}\left(\mathrm{p1}\right)$  Maximum Likelihood Estimation

 > $\mathrm{P}≔\mathrm{unapply}\left(\mathrm{ProbabilityDensityFunction}\left(\mathrm{Weibull}\left(\mathrm{alpha},\mathrm{beta}\right),\mathrm{t}\right),\mathrm{t},\mathrm{alpha},\mathrm{beta}\right)$
 ${P}{≔}\left({t}{,}{\mathrm{\alpha }}{,}{\mathrm{\beta }}\right){↦}\left\{\begin{array}{cc}{0}& {t}{<}{0}\\ \frac{{\mathrm{\beta }}{}{{t}}^{{-}{1}{+}{\mathrm{\beta }}}{}{{ⅇ}}^{{-}{\left(\frac{{t}}{{\mathrm{\alpha }}}\right)}^{{\mathrm{\beta }}}}}{{{\mathrm{\alpha }}}^{{\mathrm{\beta }}}}& {\mathrm{otherwise}}\end{array}\right\$ (3.1)
 > $\mathrm{maxLike}:=\left(\mathrm{\alpha },\mathrm{\beta }\right)\to \mathrm{add}\left(\mathrm{ln}\left(\mathrm{P}\left({\mathrm{sigWaveHeight}}_{\mathrm{i}},\mathrm{\alpha },\mathrm{\beta }\right)\right),\mathrm{i}=1..\mathrm{n}\right):$
 > $\mathrm{resultsMLE}≔\mathrm{Maximize}\left(\mathrm{maxLike}\left(\mathrm{\alpha },\mathrm{\beta }\right),\mathrm{α}=0.01..5,\mathrm{β}=0.01..5\right)$
 ${\mathrm{resultsMLE}}{≔}\left[{-4839.27465547207703}{,}\left[{\mathrm{\alpha }}{=}{1.34452570778020}{,}{\mathrm{\beta }}{=}{2.83250005643047}\right]\right]$ (3.2)
 > Moment Matching

 > $\mathrm{resultsMM}:=\mathrm{fsolve}\left(\left[\mathrm{Moment}\left(\mathrm{sigWaveHeight},1\right)=\mathrm{Moment}\left(\mathrm{Weibull}\left(\mathrm{α},\mathrm{β}\right),1\right),\mathrm{Moment}\left(\mathrm{sigWaveHeight},2\right)=\mathrm{Moment}\left(\mathrm{Weibull}\left(\mathrm{α},\mathrm{β}\right),2\right)\right],\left\{\mathrm{α}=1,\mathrm{β}=1\right\}\right)$
 ${\mathrm{resultsMM}}{≔}\left\{{\mathrm{\alpha }}{=}{1.342796022}{,}{\mathrm{\beta }}{=}{2.958762705}\right\}$ (4.1)
 > Results

 > $\mathrm{display}\left(\mathrm{p1},\mathrm{p2},\mathrm{p3},\mathrm{size}=\left[800,500\right]\right)$ >