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  • Description of locdetrend
    data locally detrended data CROSS REFERENCE INFORMATION This function calls runline Running line fit local linear regression This function is called by SOURCE CODE 0001 function data locdetrend data Fs movingwin 0002 Remove running line fit using local linear regression continuous 0003 processes 0004 Usage data locdetrend data Fs movingwin 0005 Inputs 0006 Note that units of Fs movinwin have to be consistent 0007 data data as a matrix times x channels or a single vector 0008 Fs sampling frequency optional Default 1 0009 movingwin length of moving window and stepsize window winstep optional 0010 Default window full length of data global detrend 0011 winstep window global detrend 0012 0013 Output 0014 data locally detrended data 0015 data change row to column data 0016 N C size data 0017 if nargin 2 isempty Fs Fs 1 end 0018 if nargin 3 isempty movingwin movingwin N Fs N Fs end 0019 Tw movingwin 1 Ts movingwin 2 0020 if Ts Tw error Use step size shorter than window size end 0021 n round Fs Tw 0022 dn round Fs Ts 0023 if isreal data 0024 yr real data 0025 yi imag data 0026 if n N 0027 yr detrend yr 0028

    Original URL path: http://www.chronux.org/Documentation/chronux/spectral_analysis/continuous/locdetrend.html (2015-03-27)
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  • Description of rtf
    0059 cputime 0060 flag save 0061 1 0062 name of file 0063 0064 0065 set ai UserData remark 0066 0067 0068 0069 0070 START TO RECORD 0071 fprintf To stop the program set stop 1 or press q in the figure window n 0072 start ai 0073 0074 0075 0076 0077 0078 0079 THE MAIN PROGRAM 0080 0081 0082 0083 0084 0085 0086 0087 0088 0089 0090 0091 0092 0093 CALLBACK FUNCTIONS 0094 0095 0096 0097 0098 Keypress callback 0099 function keypress src e 0100 keypressed get gcf CurrentCharacter 0101 0102 ignore raw control shift alt keys 0103 if keypressed 0104 Quit 0105 if strcmp keypressed q 0106 evalin base stop 1 0107 end 0108 end 0109 return 0110 0111 0112 FLAG FUNCTION 0113 This function activated when we capture 0114 certain amount of samples 0115 function flag obj event 0116 0117 CHECK FOR STOP SIGNAL 0118 if evalin base stop 0119 stop obj 0120 end 0121 0122 GET THE OLD DATA 0123 remark get obj UserData 0124 flag write remark 1 Do I have to 0125 buffer remark 3 What is the old picture 0126 flag save remark 7 Are we in saving mode 0127 fid remark 8 What file descriptor to save 0128 0129 0130 IN CASE DELETE SAVE THE OLD DATA 0131 0132 if flag write 20 0133 0134 0135 IN CASE WE HAVE TO SAVE CLOSE THE OLD FILE AND MAKE A NEW 0136 if flag save 0 0137 fclose fid 0138 name of data sprintf s d dat dat round cputime 1000 0139 fid fopen name of data w 0140 end 0141 0142 DELETE OLD DATA 0143 flag write 1 0144 buffer 0145 remark 1 flag write SET THE POSITION OF THE READING SHIFT 0146 end 0147 0148 0149 0150 0151 TAKE THE NEW DATA

    Original URL path: http://www.chronux.org/Documentation/chronux/spectral_analysis/specscope/rtf.html (2015-03-27)
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  • Description of aicplot
    INFORMATION This function calls aic This function is called by SOURCE CODE 0001 function g aicplot alpha varargin 0002 0003 Computes and plots the 2 AIC 0004 for local fits with different smoothing parameters 0005 0006 The first argument to aicplot alpha should be a matrix with one 0007 or two columns first column nearest neighbor component second 0008 column constant component Each row of this matrix is in turn

    Original URL path: http://www.chronux.org/Documentation/chronux/locfit/m/aicplot.html (2015-03-27)
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  • Description of fig4_2
    2 Author Catherine Loader Local Likelihood Logistic Regression for the Henderson Shepherd Mortality Data CROSS REFERENCE INFORMATION This function calls This function is called by runbook SOURCE CODE 0001 Local Regression and Likelihood Figure 4 2 0002 Author Catherine Loader 0003 0004 Local Likelihood Logistic Regression for the 0005 Henderson Shepherd Mortality Data 0006 0007 load morths 0008 fit locfit age deaths weights n family binomial alpha 0 5 0009

    Original URL path: http://www.chronux.org/Documentation/chronux/locfit/Book/fig4_2.html (2015-03-27)
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  • Description of locfit
    of the independent or predictor variables 0022 Rows of x represent subjects columns represent variables 0023 Generally local regression would be used with 1 4 independent 0024 variables In higher dimensions the curse of dimensionality 0025 as well as the difficulty of visualizing higher dimensional 0026 surfaces may limit usefulness 0027 0028 y is the column vector of the dependent or response variable 0029 For density families y is omitted 0030 NOTE x and y are the first two arguments All other arguments require 0031 the name value notation 0032 0033 weights Prior weights for observations reciprocal of variance or 0034 sample size 0035 cens Censoring indicators for hazard rate or censored regression 0036 The coding is 1 or TRUE for a censored observation and 0037 0 or FALSE for uncensored observations 0038 base Baseline parameter estimate If a baseline is provided 0039 the local regression model is fitted as 0040 Y i b i m x i epsilon i 0041 with Locfit estimating the m x term For regression models 0042 this effectively subtracts b i from Y i The advantage of the 0043 base formulation is that it extends to likelihood 0044 regression models 0045 scale A scale to apply to each variable This is especially 0046 important for multivariate fitting where variables may be 0047 measured in non comparable units It is also used to specify 0048 the frequency for variables with the a angular style 0049 sty Character string length d of styles for each predictor variable 0050 n denotes normal a denotes angular or periodic l and r 0051 denotes one sided left and right c is conditionally parametric 0052 0053 0054 Smoothing Parameters and Bandwidths 0055 The bandwidth or more accurately half width of the smoothing window 0056 controls the amount of smoothing Locfit allows specification of constant 0057 fixed nearest neighbor certain locally adaptive variable bandwidths 0058 and combinations of these Also related to the smoothing parameter 0059 are the local polynmial degree and weight function 0060 0061 nn Nearest neighbor smoothing parameter Specifying nn 0 5 0062 means that the width of each smoothing neighborhood is chosen 0063 to cover 50 of the data 0064 0065 h A constant or fixed bandwidth parameter For example h 2 0066 means that the smoothing windows have constant half width 0067 or radius 2 Note that h is applied after scaling 0068 0069 pen penalty parameter for adaptive smoothing Needs to be used 0070 with care 0071 0072 alpha The old way of specifying smoothing parameters as used in 0073 my book alpha is equivalent to the vector nn h pen 0074 If multiple componenents are non zero the largest corresponding 0075 bandwidth is used The default if none of alpha nn h pen 0076 are provided is 0 7 0 0 0077 0078 deg Degree of local polynomial Default 2 local quadratic 0079 Degrees 0 to 3 are supported by almost all parts of the 0080 Locfit code Higher degrees may work in some cases 0081 0082 kern Weight function default tcub Other choices are 0083 rect trwt tria epan bisq and gauss 0084 Choices may be restricted when derivatives are 0085 required e g for confidence bands and some bandwidth 0086 selectors 0087 0088 kt Kernel type sph default prod In multivariate 0089 problems prod uses a simplified product model which 0090 speeds up computations 0091 0092 acri Criterion for adaptive bandwidth selection 0093 0094 0095 Derivative Estimation 0096 Generally I recommend caution when using derivative estimation 0097 and especially higher order derivative estimation can you 0098 really estimate derivatives from noisy data Any derivative 0099 estimate is inherently more dependent on an assumed smoothness 0100 expressed through the bandwidth than the data Warnings aside 0101 0102 deriv Derivative estimation deriv 1 specifies the first derivative 0103 or more correctly an estimate of the local slope is returned 0104 deriv 1 1 specifies the second derivative For bivariate fits 0105 deriv 2 specifies the first partial derivative wrt x2 0106 deriv 1 2 is mixed second order derivative 0107 0108 Fitting family 0109 family is used to specify the local likelihood family 0110 Regression type families are gaussian binomial 0111 poisson gamma and geom If the family is preceded 0112 by a q e g qgauss or qpois then quasi likelihood is 0113 used in particular a dispersion estimate is computed 0114 Preceding by an r makes an attempt at robust outlier resistant 0115 estimation Combining q and r e g family qrpois may 0116 work if you re lucky 0117 Density estimation type families are dens rate and hazard 0118 hazard or failure rate Note that dens scales the output 0119 to be a statistical density estimate i e scaled to integrate 0120 to 1 rate estimates the rate or intensity function events 0121 per unit time or events per unit area which may be called 0122 density in some fields 0123 The default family is qgauss if a response y argument has been 0124 provided and dens if no response is given 0125 link Link function for local likelihood fitting Depending on the 0126 family choices may be ident log logit 0127 inverse sqrt and arcsin 0128 0129 Evaluation structures 0130 By default locfit chooses a set of points depending on the data 0131 and smoothing parameters to evaluate at This is controlled by 0132 the evaluation structure 0133 ev Specify the evaluation structure Default is tree 0134 Other choices include phull triangulation grid a grid 0135 of points data each data point crossval data 0136 but use leave one out cross validation none no evaluation 0137 points effectively producing the global parametric fit 0138 Alternatively a vector matrix of evaluation points may be 0139 provided 0140 kd trees not currently supported in mlocfit 0141 ll and ur row vectors specifying the upper and lower limits 0142 for the bounding box used by the evaluation structure 0143 They default to the data range 0144 mg For the grid evaluation structure mg

    Original URL path: http://www.chronux.org/Documentation/chronux/locfit/m/locfit.html (2015-03-27)
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  • Description of runbook
    Local Regression and Likelihood Figure 2 6 fig2 7 Local Regression and Likelihood Figure 2 7 fig3 1 Local Regression and Likelihood Figure 3 1 fig4 1 Local Regression and Likelihood Figure 4 1 fig4 2 Local Regression and Likelihood Figure 4 2 fig4 3 Local Regression and Likelihood Figure 4 3 fig4 4 Local Regression and Likelihood Figure 4 4 fig5 1 Local Regression and Likelihood Figure 5 1 fig5 2 Local Regression and Likelihood Figure 5 2 fig5 3 Local Regression and Likelihood Figure 5 3 fig5 4 Local Regression and Likelihood Figure 5 4 fig5 5 Local Regression and Likelihood Figure 5 5 fig5 6 Local Regression and Likelihood Figure 5 6 fig6 1 Local Regression and Likelihood Figure 6 1 fig6 2 Local Regression and Likelihood Figure 6 2 fig6 3 Local Regression and Likelihood Figure 6 3 fig6 4 Local Regression and Likelihood Figure 6 4 fig6 5 Local Regression and Likelihood Figure 6 5 fig6 6 Local Regression and Likelihood Figure 6 6 fig6 7 Local Regression and Likelihood Figure 6 6 fig7 1 Local Regression and Likelihood Figure 7 1 fig7 2 Local Regression and Likelihood Figure 7 2 fig7 3 Local Regression and Likelihood Figure 7 3 fig7 4 Local Regression and Likelihood Figure 7 4 fig7 5 Local Regression and Likelihood Figure 7 5 fig7 6 Local Regression and Likelihood Figure 7 6 fig8 1 Local Regression and Likelihood Figure 8 1 fig8 2 Local Regression and Likelihood Figure 8 2 fig8 3 Local Regression and Likelihood Figure 8 3 fig9 1 Local Regression and Likelihood Figure 9 1 fig9 2 Local Regression and Likelihood Figure 9 2 This function is called by SOURCE CODE 0001 fig1 1 0002 fig1 2 0003 fig2 2 0004 fig2 3 0005 fig2 4 0006

    Original URL path: http://www.chronux.org/Documentation/chronux/locfit/Book/runbook.html (2015-03-27)
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  • Description of auto_classify
    GUIDATA 0260 0261 handles output 0 0262 guidata hObject handles 0263 uiresume handles figure1 0264 0265 Executes on button press in AcceptButton 0266 function AcceptButton Callback hObject eventdata handles 0267 hObject handle to AcceptButton see GCBO 0268 eventdata reserved to be defined in a future version of MATLAB 0269 handles structure with handles and user data see GUIDATA 0270 0271 handles output handles classification 0272 guidata hObject handles 0273 uiresume handles figure1 0274 0275 0276 function CepstralEdit Callback hObject eventdata handles 0277 hObject handle to CepstralEdit see GCBO 0278 eventdata reserved to be defined in a future version of MATLAB 0279 handles structure with handles and user data see GUIDATA 0280 0281 Hints get hObject String returns contents of CepstralEdit as text 0282 str2double get hObject String returns contents of CepstralEdit as a double 0283 0284 0285 Executes during object creation after setting all properties 0286 function CepstralEdit CreateFcn hObject eventdata handles 0287 hObject handle to CepstralEdit see GCBO 0288 eventdata reserved to be defined in a future version of MATLAB 0289 handles empty handles not created until after all CreateFcns called 0290 0291 Hint edit controls usually have a white background on Windows 0292 See ISPC and COMPUTER 0293 if ispc 0294 set hObject BackgroundColor white 0295 else 0296 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0297 end 0298 0299 0300 0301 function MinClusters Callback hObject eventdata handles 0302 hObject handle to MinClusters see GCBO 0303 eventdata reserved to be defined in a future version of MATLAB 0304 handles structure with handles and user data see GUIDATA 0305 0306 Hints get hObject String returns contents of MinClusters as text 0307 str2double get hObject String returns contents of MinClusters as a double 0308 0309 0310 Executes during object creation after setting all properties 0311 function MinClusters CreateFcn hObject eventdata handles 0312 hObject handle to MinClusters see GCBO 0313 eventdata reserved to be defined in a future version of MATLAB 0314 handles empty handles not created until after all CreateFcns called 0315 0316 Hint edit controls usually have a white background on Windows 0317 See ISPC and COMPUTER 0318 if ispc 0319 set hObject BackgroundColor white 0320 else 0321 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0322 end 0323 0324 0325 0326 function MaxClusters Callback hObject eventdata handles 0327 hObject handle to MaxClusters see GCBO 0328 eventdata reserved to be defined in a future version of MATLAB 0329 handles structure with handles and user data see GUIDATA 0330 0331 Hints get hObject String returns contents of MaxClusters as text 0332 str2double get hObject String returns contents of MaxClusters as a double 0333 0334 0335 Executes during object creation after setting all properties 0336 function MaxClusters CreateFcn hObject eventdata handles 0337 hObject handle to MaxClusters see GCBO 0338 eventdata reserved to be defined in a future version of MATLAB 0339 handles empty handles not created until after all CreateFcns called 0340 0341 Hint edit controls usually have a white background on Windows 0342 See ISPC and COMPUTER 0343 if ispc 0344 set hObject BackgroundColor white 0345 else 0346 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0347 end 0348 0349 0350 Executes on selection change in TransformPopupMenu 0351 function TransformPopupMenu Callback hObject eventdata handles 0352 hObject handle to TransformPopupMenu see GCBO 0353 eventdata reserved to be defined in a future version of MATLAB 0354 handles structure with handles and user data see GUIDATA 0355 0356 Hints contents get hObject String returns TransformPopupMenu contents as cell array 0357 contents get hObject Value returns selected item from TransformPopupMenu 0358 0359 value get hObject Value 0360 0361 if value 2 0362 handles matrix2classify 1 log handles matrix2classify 1 0363 else 0364 handles matrix2classify 1 exp handles matrix2classify 1 0365 end 0366 0367 Executes during object creation after setting all properties 0368 function TransformPopupMenu CreateFcn hObject eventdata handles 0369 hObject handle to TransformPopupMenu see GCBO 0370 eventdata reserved to be defined in a future version of MATLAB 0371 handles empty handles not created until after all CreateFcns called 0372 0373 Hint popupmenu controls usually have a white background on Windows 0374 See ISPC and COMPUTER 0375 if ispc 0376 set hObject BackgroundColor white 0377 else 0378 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0379 end 0380 0381 function KClasses Callback hObject eventdata handles 0382 hObject handle to KClasses see GCBO 0383 eventdata reserved to be defined in a future version of MATLAB 0384 handles structure with handles and user data see GUIDATA 0385 0386 Hints get hObject String returns contents of KClasses as text 0387 str2double get hObject String returns contents of KClasses as a double 0388 0389 0390 Executes during object creation after setting all properties 0391 function KClasses CreateFcn hObject eventdata handles 0392 hObject handle to KClasses see GCBO 0393 eventdata reserved to be defined in a future version of MATLAB 0394 handles empty handles not created until after all CreateFcns called 0395 0396 Hint edit controls usually have a white background on Windows 0397 See ISPC and COMPUTER 0398 if ispc 0399 set hObject BackgroundColor white 0400 else 0401 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0402 end 0403 0404 0405 Executes on selection change in CepstralPopupMenu 0406 function CepstralPopupMenu Callback hObject eventdata handles 0407 hObject handle to CepstralPopupMenu see GCBO 0408 eventdata reserved to be defined in a future version of MATLAB 0409 handles structure with handles and user data see GUIDATA 0410 0411 Hints contents get hObject String returns CepstralPopupMenu contents as cell array 0412 contents get hObject Value returns selected item from CepstralPopupMenu 0413 0414 0415 Executes during object creation after setting all properties 0416 function CepstralPopupMenu CreateFcn hObject eventdata handles 0417 hObject handle to CepstralPopupMenu see GCBO 0418 eventdata reserved to be defined in a future version of MATLAB 0419 handles empty handles not created until after all CreateFcns called 0420 0421 Hint popupmenu controls usually have a white background on Windows 0422 See ISPC and COMPUTER 0423 if ispc 0424 set hObject BackgroundColor white 0425 else 0426 set hObject BackgroundColor get 0 defaultUicontrolBackgroundColor 0427 end 0428 0429 0430 0431 Executes on button press in

    Original URL path: http://www.chronux.org/Documentation/chronux/wave_browser/auto_classify.html (2015-03-27)
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  • Description of fig4_3
    Residual plots for local likelihood 0011 plot age residuals fit dev 0012 xlabel Age 0013 ylabel Residual 0014 title Deviance Residuals 0015 hold on 0016 plot min age max age 0 0 0017 hold off 0018 0019 figure Name fig4 3b Residual plots for local likelihood 0020 plot age residuals fit pear 0021 xlabel Age 0022 ylabel Residual 0023 title Pearson Residuals 0024 hold on 0025 plot min age max

    Original URL path: http://www.chronux.org/Documentation/chronux/locfit/Book/fig4_3.html (2015-03-27)
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