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Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%

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Presentation on theme: "Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%"— Presentation transcript:

1 Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%

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4 %nakedsoftware.org opensource license, copyright 2010 % %developed by Stephane Poirier, M.Sc. Optical Physics, Remote Sensing Application Software Developer ( ) % %this function is part of oifii.org's ar\sp\ Microwave- derived 30-year Canada-Alaska Daily Temperature and Snowcover Databases library % %this function is part of oifii.org's ar\sp\'this folder' application (lauched with ar\sp\'this file'.m) %oifii.org's ar\sp\affiche_carte application is part of the oifii.org's ar\sp set of applications which %may also contain similar variant versions of this function with identical filename. % %A geophysical research paper about this work has been submitted in June 2009 for publication in JGR-Atmosphere %Royer, A. and Poirier S., Surface temperature spatial and temporal variations in North America from homogenized %satellite SMMR-SSM/I microwave measurements and reanalysis for , Journal of Geophysical Research - Atmosphere, %Submitted June 2009, Poirier_Microwave-derived-daily-surface- temperature_JGR2009JD012760_R2.pdf % %This study's database can be downloaded from the author web site at: %http://www.oifii.org/tsatdb/Royer-Poirier_Microwave-derived- daily-surface-temperature-db_ zip % %this function is used to display the raw microwave raster data (NSIDC's SMMR and SSMI satellite, ref. nsidc.org) % %usage: % 20yymmmdd % %version 0.0, 20yymmmdd, spi, initial function draft % %nakedsoftware.org opensource license, copyright 2010

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6 fct matlab qui renvoie le signification statistique du test de student sur une série Y

7 function [t_student]=student(x,y) if(length(x)~=length(y)) return; end n=length(x); dl=n-2; % coef des polynomes 1 er ordre % y = ax + b [p,s]=polyfit(x,y,1) ; a=p(1,1); b=p(1,2); % coefficient de correlation r = corrcoef(x,y) ; r = r(1,2) ; % ecart type residuel syx = sum(y.*y) - (sum(y)*sum(y)/n) ; syx = syx - a*a*(sum(x.*x)-(sum(x)*sum(x)/n)) ; syx = sqrt(syx/dl) ; % ecart type de y sy=syx/sqrt(1-r*r) ; % estimateur de ecart type de la pente Sa = a * sqrt((1-r*r)/(r*r*(dl))); delta_a = 1.96 * abs(Sa / sqrt(dl)); % sur la pente (si on veut comparer par rapport au coef beta0) % H0 : hypothèse d'une pente == à 0 pente0=0; t_pente=(a-pente0)/Sa ; % sur la droite de régression % disp(['hypothese de la pente : pente = ',num2str(pente0)]); % disp(['hypothese rejetee si : ',num2str(t_pente),... % ' > t de student ']); % % % TEST pour connaitre le % de signification % % MATRICE DE STUDENT % ne contient pas pour 1 degré de liberté student(1,:)= [ ] ; student(2,:)=[ ] ; student(3,:)=[ ] ; student(4,:)=[ ] ; student(5,:)=[ ] ; student(6,:)=[ ] ; student(7,:)=[ ] ; student(8,:)=[ ] ; student(9,:)=[ ] ; student(10,:)=[ ] ; student(11,:)=[ ] ; student(12,:)=[ ] ; student(13,:)=[ ] ; student(14,:)=[ ] ; student(15,:)=[ ] ; student(16,:)=[ ] ; student(17,:)=[ ] ; student(18,:)=[ ] ; student(19,:)=[ ] ; student(20,:)=[ ] ; student(21,:)=[ ] ; student(22,:)=[ ] ; student(23,:)=[ ] ; student(24,:)=[ ] ; student(25,:)=[ ] ; student(26,:)=[ ] ; student(27,:)=[ ] ; student(28,:)=[ ] ; student(29,:)=[ ] ; student(30,:)=[ ] ; %see schaum series formulas and mathematic tables page 258 %for extra values of n. It provides all the herein included %as well as 40, 60, 120 and infinity. if ~isempty(find(student(dl,:)<=t_pente)) t_student=find(student(dl,:)<=t_pente); t_student=t_student(1,1); %taking the first (highest percentil) result from t_student t_student=student(1,t_student); else t_student=0; end


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