ACDC 2019 Naturalist
Analysis 04 : Détails of pre-analyses
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Results: main figures Previous analysis Back to global report Next analysis

Study type: Point transect, Radial distance, No clustering.

Units used: Meter for distances, Sq. Kilometer for areas.

Note: Most figures have been rounded for readability, but 'CoefVar Density' have been further modified : converted to %

Echant Espèce Passage Adulte Durée Mod Key Fn Mod Adj Ser ExCod NObs Max Dist Effort AIC Chi2 P KS P CoefVar Density Density Min Density Max Density Number Min Number Max Number EDR/ESW Min EDR/ESW Max EDR/ESW PDetec Min PDetec Max PDetec RunFolder
04 3 Prunella modularis a+b m 10mn UNIFORM COSINE 2 47 271.221 190 494.6 0.21 0.47 24.2 6.24 3.89 9.99 150 93 240 112.4 95.3 132.5 0.172 0.124 0.238 PrunModu-ab-10mn-m-uni-cos-f3smf1_a
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Results: all details Previous analysis Back to global report Next analysis

Study type: Point transect, Radial distance, No clustering.

Units used: Meter for distances, Sq. Kilometer for areas.

Note: All values have been left untouched, as output by MCDS (no rounding, no conversion)

Echant Espèce Passage Adulte Durée Abrev. Echant NTot Obs Min Dist Max Dist Mod Key Fn Mod Adj Ser Mod Chc Crit Conf Interv ExCod StartTime ElapsedTime RunFolder NObs NSamp Effort EncRate CoefVar EncRate Min EncRate Max EncRate DoF EncRate Left Trunc Right Trunc Obs Rate TotNum Pars Delta AIC AIC Chi2 P Chi2 P 1 Chi2 P 2 Chi2 P 3 f/h(0) CoefVar f/h(0) Min f/h(0) Max f/h(0) DoF f/h(0) PDetec CoefVar PDetec Min PDetec Max PDetec DoF PDetec EDR/ESW CoefVar EDR/ESW Min EDR/ESW Max EDR/ESW DoF EDR/ESW AICc BIC LogLhood KS P CvM Uw P CvM Cw P Key Fn Adj Ser NumPars KeyFn NumPars AdjSer Num Covars EstA(1) EstA(2) DensClu CoefVar DensClu Min DensClu Max DensClu DoF DensClu Density Delta CoefVar Density CoefVar Density Min Density Max Density DoF Density Number CoefVar Number Min Number Max Number DoF Number Qual Bal 1 Qual Bal 2 Qual Bal 3 Qual Chi2+ Qual KS+ Qual DCv+
04 3 Prunella modularis a+b m 10mn PrunModu-ab-10mn-m 47.000000 10.176839 271.221090 UNIFORM COSINE AIC 95 2 2023-04-16 18:55:40.254027 0.523999 PrunModu-ab-10mn-m-uni-cos-f3smf1_a 47.000000 96.000000 190.000000 0.247368 0.177070 0.174524 0.350618 95.000000 0.000000 271.221100 100.000000 2.000000 0.000000 494.608800 0.212556 0.365375 0.041433 0.212556 0.000158 0.164232 0.000114 0.000220 45.000000 0.171655 0.164232 0.123582 0.238429 45.000000 112.370500 0.082116 95.267530 132.543800 45.000000 494.881600 498.309100 -245.304400 0.473960 0.600000 0.600000 UNIFORM COSINE 0.000000 2.000000 0.000000 1.331354 0.351025 6.235769 0.241508 3.893096 9.988147 128.303600 6.235769 0.000000 0.241508 3.893096 9.988147 128.303600 150.000000 0.241508 93.000000 240.000000 128.303600 0.563369 0.522783 0.516768 0.468195 0.511827 0.487815
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Summary computation log Previous analysis Back to global report Next analysis

This is mcds.exe version 6.2.0     
 Options;                                                                      
 Type=Point;                                                                   
 Distance=Radial /Measure='Meter';                                             
 Area /Units='Sq. Kilometer';                                                  
 Object=Single;                                                                
 SF=1;                                                                         
 Selection=Sequential;                                                         
 Lookahead=1;                                                                  
 Maxterms=5;                                                                   
 Confidence=95;                                                                
 print=Selection;                                                              
 End;                                                                          
 Data /Structure=Flat;                                                         
 Fields=STR_LABEL,STR_AREA,SMP_LABEL,SMP_EFFORT,DISTANCE;                      
 Infile=pranlys\230416-180310\PrunModu-ab-10mn-m-uni-cos-f3smf1_a\data.txt /NoEcho;                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              
 Data will be input from file - [...]MN-M-UNI-COS-F3SMF1_A\DATA.TXT
 End;                                                                          
 Dataset has been stored.
 Estimate;                                                                     
 Distance;                                                                     
 Density=All;                                                                  
 Encounter=All;                                                                
 Detection=All;                                                                
 Size=All;                                                                     
 Estimator /Key=UNIFORM /Adjust=COSINE /Criterion=AIC;                         
 Monotone=Strict;                                                              
 Pick=AIC;                                                                     
 GOF;                                                                          
 Cluster /Bias=GXLOG;                                                          
 VarN=Empirical;                                                               
 End;                                                                          
      ** Warning: Parameters are being constrained to obtain monotonicity. **
      ** Warning: Parameters are being constrained to obtain monotonicity. **
---

Detailed computation log

Estimation Options Listing Previous analysis Back to global report Next analysis

 Parameter Estimation Specification
 ----------------------------------
 Encounter rate for all data combined
 Detection probability for all data combined
 Density for all data combined

 Distances:
 ----------
 Analysis based on exact distances
 Width: use largest measurement/last interval endpoint

 Estimators:
 -----------
 Estimator  1
 Key: Uniform
 Adjustments - Function                 : Cosines
             - Term selection mode      : Sequential
             - Term selection criterion : Akaike Information Criterion (AIC)
             - Distances scaled by      : W (right truncation distance)

 Estimator selection: Choose estimator with minimum  AIC
 Estimation functions: constrained to be nearly monotone non-increasing

 Variances:
 ----------
 Variance of n: Empirical estimate from sample
                (design-derived estimator R2/P2)
 Variance of f(0): MLE estimate

 Goodness of fit:
 ----------------
 Cut points chosen by program

 Glossary of terms
 -----------------

 Data items:
 n    - number of observed objects (single or clusters of animals)
 L    - total length of transect line(s) 
 k    - number of samples
 K    - point transect effort, typically K=k
 T    - length of time searched in cue counting
 ER   - encounter rate (n/L or n/K or n/T)
 W    - width of line transect or radius of point transect
 x(i) - distance to i-th observation
 s(i) - cluster size of i-th observation
 r-p  - probability for regression test
 chi-p- probability for chi-square goodness-of-fit test

 Parameters or functions of parameters:
 m    - number of parameters in the model
 A(I) - i-th parameter in the estimated probability density function(pdf)
 f(0) - 1/u = value of pdf at zero for line transects
 u    - W*p = ESW, effective detection area for line transects
 h(0) - 2*PI/v
 v    - PI*W*W*p, is the effective detection area for point transects
 p    - probability of observing an object in defined area
 ESW  - for line transects, effective strip width = W*p
 EDR  - for point transects, effective detection radius  = W*sqrt(p)
 rho  - for cue counts, the cue rate
 DS   - estimate of density of clusters
 E(S) - estimate of expected value of cluster size
 D    - estimate of density of animals
 N    - estimate of number of animals in specified area

        

Detection Fct/Global/Model Fitting Previous analysis Back to global report Next analysis

 Effort        :    190.0000    
 # samples     :    96
 Width         :    271.2211    
 # observations:    47

 Model  1
    Uniform key, k(y) = 1/W
       Results:
       Convergence was achieved with    1 function evaluations.
       Final Ln(likelihood) value =  -285.35577    
       Akaike information criterion =   570.71155    
       Bayesian information criterion =   570.71155    
       AICc =   570.71155    
       Final parameter values:

 Model  2
    Uniform key, k(y) = 1/W
    Cosine adjustments of order(s) :  1
       Results:
       Convergence was achieved with   24 function evaluations.
       Final Ln(likelihood) value =  -252.28137    
       Akaike information criterion =   506.56274    
       Bayesian information criterion =   508.41290    
       AICc =   506.65164    
       Final parameter values:  0.97570701

    Likelihood ratio test between models  1 and  2
       Likelihood ratio test value    =    66.1488
       Probability of a greater value =   0.000000
 *** Model  2 selected over model  1 based on minimum AIC

 Model  3
    Uniform key, k(y) = 1/W
    Cosine adjustments of order(s) :  1, 2
       Results:
       Convergence was achieved with   33 function evaluations.
       Final Ln(likelihood) value =  -245.30442    
       Akaike information criterion =   494.60883    
       Bayesian information criterion =   498.30914    
       AICc =   494.88156    
       Final parameter values:   1.3313540     0.35102447    
      ** Warning: Parameters are being constrained to obtain monotonicity. **

    Likelihood ratio test between models  2 and  3
       Likelihood ratio test value    =    13.9539
       Probability of a greater value =   0.000187
 *** Model  3 selected over model  2 based on minimum AIC

 Model  4
    Uniform key, k(y) = 1/W
    Cosine adjustments of order(s) :  1, 2, 3
       Results:
       Convergence was achieved with   16 function evaluations.
       Final Ln(likelihood) value =  -527.06363    
       Akaike information criterion =   1060.1273    
       Bayesian information criterion =   1065.6777    
       AICc =   1060.6854    
       Final parameter values:   61575.195     -27718.076     -61572.895    
      ** Warning: Parameters are being constrained to obtain monotonicity. **

    Likelihood ratio test between models  3 and  4
       Likelihood ratio test value    =  -563.5184
       Probability of a greater value =   1.000000
 *** Model  3 selected over model  4 based on minimum AIC              

        

Detection Fct/Global/Parameter Estimates Previous analysis Back to global report Next analysis

 Effort        :    190.0000    
 # samples     :    96
 Width         :    271.2211    
 # observations:    47

 Model
    Uniform key, k(y) = 1/W
    Cosine adjustments of order(s) :  1, 2

              Point        Standard    Percent Coef.        95 Percent
  Parameter   Estimate       Error      of Variation     Confidence Interval
  ---------  -----------  -----------  --------------  ----------------------
    A( 1)      1.331       0.1018    
    A( 2)     0.3510       0.1000    
    h(0)     0.15839E-03  0.26013E-04      16.42      0.11403E-03  0.22000E-03
    p        0.17166      0.28191E-01      16.42      0.12358      0.23843    
    EDR       112.37       9.2274           8.21       95.268       132.54    
  ---------  -----------  -----------  --------------  ----------------------

 Sampling Correlation of Estimated Parameters

         A( 1)   A( 2)
 A( 1)  1.000   0.981
 A( 2)  0.981   1.000

        

Detection Fct/Global/Plot: Qq-plot Previous analysis Back to global report Next analysis

Detection Fct/Global/K-S GOF Test Previous analysis Back to global report Next analysis

 Kolmogorov-Smirnov test
 -----------------------

 D_n                      = 0.1232                 p  = 0.4740

 Cramer-von Mises family tests
 -----------------------------

 W-sq (uniform weighting) = 0.1046          0.500 < p <= 0.600
   Relevant critical values:
     W-sq crit(alpha=0.600) = 0.0974
     W-sq crit(alpha=0.500) = 0.1193

 C-sq (cosine weighting)  = 0.0668          0.500 < p <= 0.600
   Relevant critical values:
     C-sq crit(alpha=0.600) = 0.0625
     C-sq crit(alpha=0.500) = 0.0773

        

Detection Fct/Global/Plot: Detection Probability 1 Previous analysis Back to global report Next analysis

Detection Fct/Global/Plot: Pdf 1 Previous analysis Back to global report Next analysis

Detection Fct/Global/Chi-sq GOF Test 1 Previous analysis Back to global report Next analysis

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1     0.000        67.8           16       14.65        0.125
   2      67.8        136.           24       22.97        0.047
   3      136.        203.            6        8.31        0.642
   4      203.        271.            1        1.08        0.006
 -----------------------------------------------------------------
 Total Chi-square value =     0.8193  Degrees of Freedom =  1.00

Probability of a greater chi-square value, P = 0.36538

 The program has limited capability for pooling.  The user should
 judge the necessity for pooling and if necessary, do pooling by hand.

        

Detection Fct/Global/Plot: Detection Probability 2 Previous analysis Back to global report Next analysis

Detection Fct/Global/Plot: Pdf 2 Previous analysis Back to global report Next analysis

Detection Fct/Global/Chi-sq GOF Test 2 Previous analysis Back to global report Next analysis

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1     0.000        45.2            7        7.09        0.001
   2      45.2        90.4           11       16.02        1.575
   3      90.4        136.           22       14.49        3.890
   4      136.        181.            6        7.09        0.168
   5      181.        226.            0        1.71        1.706
   6      226.        271.            1        0.59        0.284
 -----------------------------------------------------------------
 Total Chi-square value =     7.6250  Degrees of Freedom =  3.00

Probability of a greater chi-square value, P = 0.05443

 The program has limited capability for pooling.  The user should
 judge the necessity for pooling and if necessary, do pooling by hand.

 Goodness of Fit Testing with some Pooling

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1     0.000        45.2            7        7.09        0.001
   2      45.2        90.4           11       16.02        1.575
   3      90.4        136.           22       14.49        3.890
   4      136.        181.            6        7.09        0.168
   5      181.        271.            1        2.30        0.732
 -----------------------------------------------------------------
 Total Chi-square value =     6.3673  Degrees of Freedom =  2.00

Probability of a greater chi-square value, P = 0.04143

        

Detection Fct/Global/Plot: Detection Probability 3 Previous analysis Back to global report Next analysis

Detection Fct/Global/Plot: Pdf 3 Previous analysis Back to global report Next analysis

Detection Fct/Global/Chi-sq GOF Test 3 Previous analysis Back to global report Next analysis

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1     0.000        27.1            2        2.67        0.168
   2      27.1        54.2            9        7.24        0.428
   3      54.2        81.4            6        9.80        1.475
   4      81.4        108.           10        9.90        0.001
   5      108.        136.           13        7.99        3.134
   6      136.        163.            4        5.15        0.258
   7      163.        190.            2        2.56        0.121
   8      190.        217.            0        0.94        0.943
   9      217.        244.            0        0.37        0.372
  10      244.        271.            1        0.37        1.102
 -----------------------------------------------------------------
 Total Chi-square value =     8.0034  Degrees of Freedom =  7.00

Probability of a greater chi-square value, P = 0.33229

 The program has limited capability for pooling.  The user should
 judge the necessity for pooling and if necessary, do pooling by hand.

 Goodness of Fit Testing with some Pooling

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1     0.000        27.1            2        2.67        0.168
   2      27.1        54.2            9        7.24        0.428
   3      54.2        81.4            6        9.80        1.475
   4      81.4        108.           10        9.90        0.001
   5      108.        136.           13        7.99        3.134
   6      136.        163.            4        5.15        0.258
   7      163.        271.            3        4.24        0.361
 -----------------------------------------------------------------
 Total Chi-square value =     5.8256  Degrees of Freedom =  4.00

Probability of a greater chi-square value, P = 0.21256

        

Density Estimates/Global Previous analysis Back to global report Next analysis

 Effort        :    190.0000    
 # samples     :    96
 Width         :    271.2211    
 # observations:    47

 Model  3
    Uniform key, k(y) = 1/W
    Cosine adjustments of order(s) :  1, 2

              Point        Standard    Percent Coef.        95% Percent
  Parameter   Estimate       Error      of Variation     Confidence Interval
  ---------  -----------  -----------  --------------  ----------------------
    D         6.2358       1.5060          24.15       3.8931       9.9881    
    N         150.00       36.226          24.15       93.000       240.00    
  ---------  -----------  -----------  --------------  ----------------------

 Measurement Units                
 ---------------------------------
 Density: Numbers/Sq. kilometers 
     EDR: meters

 Component Percentages of Var(D)
 -------------------------------
 Detection probability   :  46.2
 Encounter rate          :  53.8

        

Estimation Summary - Encounter rates Previous analysis Back to global report Next analysis

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
                 n       47.000    
                 k       96.000    
                 K       190.00    
                 n/K    0.24737       17.71    95.00 0.17452      0.35062    
                 Left    0.0000
                 Width   271.22    

        

Estimation Summary - Detection probability Previous analysis Back to global report Next analysis

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
 Uniform/Cosine         
                 m       2.0000    
                 LnL    -245.30    
                 AIC     494.61    
                 AICc    494.88    
                 BIC     498.31    
                 Chi-p  0.21256    
                 h(0)   0.15839E-03   16.42    45.00 0.11403E-03  0.22000E-03
                 p      0.17166       16.42    45.00 0.12358      0.23843    
                 EDR     112.37        8.21    45.00  95.268       132.54    

        

Estimation Summary - Density&Abundance Previous analysis Back to global report Next analysis

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
 Uniform/Cosine         
                 D       6.2358       24.15   128.30  3.8931       9.9881    
                 N       150.00       24.15   128.30  93.000       240.00

        
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