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Chapter Contents
Chapter Introduction
NAG Toolbox

NAG Toolbox: nag_correg_optset (g02zk)

Purpose

nag_correg_optset (g02zk) either initializes or resets the optional parameter arrays or sets a single optional parameter for supported problem solving functions in Chapter G02. Currently, only nag_correg_quantile_linreg (g02qg) is supported.

Syntax

[iopts, opts, ifail] = g02zk(optstr, iopts, opts, 'liopts', liopts, 'lopts', lopts)
[iopts, opts, ifail] = nag_correg_optset(optstr, iopts, opts, 'liopts', liopts, 'lopts', lopts)

Description

nag_correg_optset (g02zk) has three purposes: to initialize optional parameter arrays, to reset all optional parameters to their default values or to set a single optional parameter to a user-supplied value.
Optional parameters and their values are, in general, presented as a character string, optstr, of the form ‘option = optval=optval’; alphabetic characters can be supplied in either upper or lower case. Both option and optvaloptval may consist of one or more tokens separated by white space. The tokens that comprise optvaloptval will normally be either an integer, real or character value as defined in the description of the specific optional argument. In addition all optional parameters can take an optvaloptval DEFAULT which resets the optional parameter to its default value.
It is imperative that optional parameter arrays are initialized before any options are set, before the relevant problem solving function is called and before any options are queried using nag_correg_optget (g02zl). To initialize the optional parameter arrays iopts and opts for a specific problem solving function, the option Initialize is used with valuevalue identifying the problem solving function to be called, via its short name. For example, to initialize optional parameter arrays to be passed to nag_correg_quantile_linreg (g02qg), nag_correg_optset (g02zk) is called as follows:
[iopts, opts, ifail] = g02zk('Initialize = g02qg', iopts, opts);
Information relating to available option names and their corresponding valid values is given in Section [Optional Parameters] in (g02qg).

References

None.

Parameters

Compulsory Input Parameters

1:     optstr – string
A string identifying the option to be set.
Initialize = function nameInitialize=function name
Initialize the optional parameter arrays iopts and opts for use with function function namefunction name, where function namefunction name is the short name of the problem solving function you wish to use.
DefaultsDefaults
Resets all options to their default values.
option = optvaloption=optval
See Section [Optional Parameters] in (g02qg) for details of valid values for option and optval. The equals sign ( = =) delimiter must be used to separate the option from its optval value.
optstr is case insensitive. Each token in the option and optval component must be separated by at least one space.
2:     iopts(liopts) – int64int32nag_int array
liopts, the dimension of the array, must satisfy the constraint unless otherwise stated in the documentation for a specific, supported, problem solving function, liopts100liopts100.
Optional parameter array.
If optstr has the form Initialize = function nameInitialize=function name, the contents of iopts need not be set.
Otherwise, iopts must not have been altered since the last call to nag_correg_optset (g02zk), nag_correg_optget (g02zl) or the selected problem solving function.
3:     opts(lopts) – double array
lopts, the dimension of the array, must satisfy the constraint unless otherwise stated in the documentation for a specific, supported, problem solving function, lopts100lopts100.
Optional parameter array.
If optstr has the form Initialize = function nameInitialize=function name, the contents of opts need not be set.
Otherwise, opts must not have been altered since the last call to nag_correg_optset (g02zk), nag_correg_optget (g02zl) or the selected problem solving function.

Optional Input Parameters

1:     liopts – int64int32nag_int scalar
Default: The dimension of the array iopts.
The length of the array iopts.
Constraint: unless otherwise stated in the documentation for a specific, supported, problem solving function, liopts100liopts100.
2:     lopts – int64int32nag_int scalar
Default: The dimension of the array opts.
The length of the array opts.
Constraint: unless otherwise stated in the documentation for a specific, supported, problem solving function, lopts100lopts100.

Input Parameters Omitted from the MATLAB Interface

None.

Output Parameters

1:     iopts(liopts) – int64int32nag_int array
Dependent on the contents of optstr, either an initialized, reset or updated version of the optional parameter array.
2:     opts(lopts) – double array
Dependent on the contents of optstr, either an initialized, reset or updated version of the optional parameter array.
3:     ifail – int64int32nag_int scalar
ifail = 0ifail=0 unless the function detects an error (see [Error Indicators and Warnings]).

Error Indicators and Warnings

Errors or warnings detected by the function:
  ifail = 11ifail=11
On entry, the option supplied in optstr was not recognized.
  ifail = 12ifail=12
On entry, the expected delimiter ‘ = =’ was not found in optstr.
  ifail = 13ifail=13
On entry, could not convert the specified optval to an integer.
On entry, could not convert the specified optval to a real.
  ifail = 14ifail=14
On entry, attempting to initialize the optional parameter arrays but specified function name was not valid.
  ifail = 15ifail=15
On entry, the optval supplied for the integer optional parameter is not valid.
  ifail = 16ifail=16
On entry, the optval supplied for the real optional parameter is not valid.
  ifail = 17ifail=17
On entry, the optval supplied for the character optional parameter is not valid.
  ifail = 21ifail=21
On entry, either the option arrays have not been initialized or they have been corrupted.
  ifail = 31ifail=31
liopts is too small.
  ifail = 51ifail=51
lopts is too small.
  ifail = 999ifail=-999
Dynamic memory allocation failed.

Accuracy

Not applicable.

Further Comments

Not applicable.

Example

function nag_correg_optset_example
sorder = int64(1);
c1 = 'y';
weight = 'u';
dat = [ 420.1577;  541.4117;  901.1575;  639.0802;  750.8756;  945.7989;
        829.3979;  979.1648; 1309.8789; 1492.3987;  502.8390;  616.7168;
        790.9225;  555.8786;  713.4412;  838.7561;  535.0766;  596.4408;
        924.5619;  487.7583;  692.6397;  997.8770;  506.9995;  654.1587;
        933.9193;  433.6813;  587.5962;  896.4746;  454.4782;  584.9989;
        800.7990;  502.4369;  713.5197;  906.0006;  880.5969;  796.8289;
        854.8791; 1167.3716;  523.8000;  670.7792;  377.0584;  851.5430;
       1121.0937;  625.5179;  805.5377;  558.5812;  884.4005; 1257.4989;
       2051.1789; 1466.3330;  730.0989; 2432.3910;  940.9218; 1177.8547;
       1222.5939; 1519.5811;  687.6638;  953.1192;  953.1192;  953.1192;
        939.0418; 1283.4025; 1511.5789; 1342.5821;  511.7980;  689.7988;
       1532.3074; 1056.0808;  387.3195;  387.3195;  410.9987;  499.7510;
        832.7554;  614.9986;  887.4658; 1595.1611; 1807.9520;  541.2006;
       1057.6767;  800.7990; 1245.6964; 1201.0002;  634.4002;  956.2315;
       1148.6010; 1768.8236; 2822.5330;  922.3548; 2293.1920;  627.4726;
        889.9809; 1162.2000; 1197.0794;  530.7972; 1142.1526; 1088.0039;
        484.6612; 1536.0201;  678.8974;  671.8802;  690.4683;  860.6948;
        873.3095;  894.4598; 1148.6470;  926.8762;  839.0414;  829.4974;
       1264.0043; 1937.9771;  698.8317;  920.4199; 1897.5711;  891.6824;
        889.6784; 1221.4818;  544.5991; 1031.4491; 1462.9497;  830.4353;
        975.0415; 1337.9983;  867.6427;  725.7459;  989.0056; 1525.0005;
        672.1960;  923.3977;  472.3215;  590.7601;  831.7983; 1139.4945;
        507.5169;  576.1972;  696.5991;  650.8180;  949.5802;  497.1193;
        570.1674;  724.7306;  408.3399;  638.6713; 1225.7890;  715.3701;
        800.4708;  975.5974; 1613.7565;  608.5019;  958.6634;  835.9426;
       1024.8177; 1006.4353;  726.0000;  494.4174;  776.5958;  415.4407;
        581.3599;  643.3571; 2551.6615; 1795.3226; 1165.7734;  815.6212;
       1264.2066; 1095.4056;  447.4479; 1178.9742;  975.8023; 1017.8522;
        423.8798;  558.7767;  943.2487; 1348.3002; 2340.6174;  587.1792;
       1540.9741; 1115.8481; 1044.6843; 1389.7929; 2497.7860; 1585.3809;
       1862.0438; 2008.8546;  697.3099;  571.2517;  598.3465;  461.0977;
        977.1107;  883.9849;  718.3594;  543.8971; 1587.3480; 4957.8130;
        969.6838;  419.9980;  561.9990;  689.5988; 1398.5203;  820.8168;
        875.1716; 1392.4499; 1256.3174; 1362.8590; 1999.2552; 1209.4730;
       1125.0356; 1827.4010; 1014.1540;  880.3944;  873.7375;  951.4432;
        473.0022;  601.0030;  713.9979;  829.2984;  959.7953; 1212.9613;
        958.8743; 1129.4431; 1943.0419;  539.6388;  463.5990;  562.6400;
        736.7584; 1415.4461; 2208.7897;  636.0009;  759.4010; 1078.8382;
        748.6413;  987.6417;  788.0961; 1020.0225; 1230.9235;  440.5174;
        743.0772];
y = [ 255.8394;  310.9587;  485.6800;  402.9974;  495.5608;  633.7978;
      630.7566;  700.4409;  830.9586;  815.3602;  338.0014;  412.3613;
      520.0006;  452.4015;  512.7201;  658.8395;  392.5995;  443.5586;
      640.1164;  333.8394;  466.9583;  543.3969;  317.7198;  424.3209;
      518.9617;  338.0014;  419.6412;  476.3200;  386.3602;  423.2783;
      503.3572;  354.6389;  497.3182;  588.5195;  654.5971;  550.7274;
      528.3770;  640.4813;  401.3204;  435.9990;  276.5606;  588.3488;
      664.1978;  444.8602;  462.8995;  377.7792;  553.1504;  810.8962;
     1067.9541; 1049.8788;  522.7012; 1424.8047;  517.9196;  830.9586;
      925.5795; 1162.0024;  383.4580;  621.1173;  621.1173;  621.1173;
      548.6002;  745.2353;  837.8005;  795.3402;  418.5976;  508.7974;
      883.2780;  742.5276;  242.3202;  242.3202;  266.0010;  408.4992;
      614.7588;  385.3184;  515.6200; 1138.1620;  993.9630;  299.1993;
      750.3202;  572.0807;  907.3969;  811.5776;  427.7975;  649.9985;
      860.6002; 1143.4211; 2032.6792;  590.6183; 1570.3911;  483.4800;
      600.4804;  696.2021;  774.7962;  390.5984;  612.5619;  708.7622;
      296.9192; 1071.4627;  496.5976;  503.3974;  357.6411;  430.3376;
      624.6990;  582.5413;  580.2215;  543.8807;  588.6372;  627.9999;
      712.1012;  968.3949;  482.5816;  593.1694; 1033.5658;  693.6795;
      693.6795;  761.2791;  361.3981;  628.4522;  771.4486;  757.1187;
      821.5970; 1022.3202;  679.4407;  538.7491;  679.9981;  977.0033;
      561.2015;  728.3997;  372.3186;  361.5210;  620.8006;  819.9964;
      360.8780;  395.7608;  442.0001;  404.0384;  670.7993;  297.5702;
      353.4882;  383.9376;  284.8008;  431.1000;  801.3518;  448.4513;
      577.9111;  570.5210;  865.3205;  444.5578;  680.4198;  576.2779;
      708.4787;  734.2356;  433.0010;  327.4188;  485.5198;  305.4390;
      468.0008;  459.8177;  863.9199;  831.4407;  534.7610;  392.0502;
      934.9752;  813.3081;  263.7100;  769.0838;  630.5863;  645.9874;
      319.5584;  348.4518;  614.5068;  662.0096; 1504.3708;  406.2180;
      692.1689;  588.1371;  511.2609;  700.5600; 1301.1451;  879.0660;
      912.8851; 1509.7812;  484.0605;  399.6703;  444.1001;  248.8101;
      527.8014;  500.6313;  436.8107;  374.7990;  726.3921; 1827.2000;
      523.4911;  334.9998;  473.2009;  581.2029;  929.7540;  591.1974;
      637.5483;  674.9509;  776.7589;  959.5170; 1250.9643;  737.8201;
      810.6772;  983.0009;  708.8968;  633.1200;  631.7982;  608.6419;
      300.9999;  377.9984;  397.0015;  588.5195;  681.7616;  807.3603;
      696.8011;  811.1962; 1305.7201;  442.0001;  353.6013;  468.0008;
      526.7573;  890.2390; 1318.8033;  331.0005;  416.4015;  596.8406;
      429.0399;  619.6408;  400.7990;  775.0209;  772.7611;  306.5191;
      522.6019];
isx = [int64(1)];
tau = [0.10; 0.25; 0.50; 0.75; 0.90];
state = zeros(1, 1, 'int64');
ip = 2;
b = zeros(2, 5);
iopts = zeros(100, 1, 'int64');
opts = zeros(100, 1);
% Initialize the optional argument array
[iopts, opts, ifail] = nag_correg_optset('Initialize = nag_correg_quantile_linreg', iopts, opts);

% Set optional arguments
[iopts, opts, ifail] = nag_correg_optset('Return Residuals = Yes', iopts, opts);
[iopts, opts, ifail] = nag_correg_optset('Matrix Returned = Covariance', iopts, opts);
[iopts, opts, ifail] = nag_correg_optset('Interval Method = IID', iopts, opts);

% Call the model fitting routine
[df, b, bl, bu, ch, res, state, info, ifail] = ...
    nag_correg_quantile_linreg(sorder, c1, weight, dat, isx, y, tau, b, iopts, opts, state);

if (ifail == 0)
  % Display the parameter estimates
  for l=1:numel(tau)
    fprintf('\nQuantile: %6.3f\n\n', tau(l));
    fprintf('        Lower   Parameter   Upper\n');
    fprintf('        Limit   Estimate    Limit\n');
    for j=1:2
      fprintf('%3d   %7.3f   %7.3f   %7.3f\n', j, bl(j,l), b(j,l), bu(j,l));
    end
    fprintf('\nCovariance matrix\n');
    for i=1:ip
      fprintf('%10.3e ', ch(1:i, i, l));
      fprintf('\n');
    end
    fprintf('\n');
  end

  if (numel(res) > 0)
    fprintf('First 10 Residuals\n');
    fprintf('                              Quantile\n');
    fprintf('Obs.   %6.3f     %6.3f     %6.3f     %6.3f     %6.3f\n', tau);
    for i=1:10
      fprintf(' %3d %10.5f %10.5f %10.5f %10.5f %10.5f\n', i, res(i, 1:5));
    end
  else
    fprintf('Residuals not returned\n');
  end
elseif (ifail == 231)
  fprintf('\nAdditional error information (info):\n');
  disp(info);
end
 

Quantile:  0.100

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    74.946   110.142   145.337
  2     0.370     0.402     0.433

Covariance matrix
 3.191e+02 
-2.541e-01  2.587e-04 


Quantile:  0.250

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    64.232    95.483   126.735
  2     0.446     0.474     0.502

Covariance matrix
 2.516e+02 
-2.004e-01  2.039e-04 


Quantile:  0.500

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    55.399    81.482   107.566
  2     0.537     0.560     0.584

Covariance matrix
 1.753e+02 
-1.396e-01  1.421e-04 


Quantile:  0.750

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    41.372    62.396    83.421
  2     0.625     0.644     0.663

Covariance matrix
 1.139e+02 
-9.068e-02  9.230e-05 


Quantile:  0.900

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    26.829    67.351   107.873
  2     0.650     0.686     0.723

Covariance matrix
 4.230e+02 
-3.369e-01  3.429e-04 

First 10 Residuals
                              Quantile
Obs.    0.100      0.250      0.500      0.750      0.900
   1  -23.10718  -38.84219  -61.00711  -77.14462  -99.86551
   2  -16.70358  -41.20981  -73.81193 -100.11463 -127.96277
   3   13.48419  -37.04518 -100.61322 -157.07478 -200.13481
   4   36.09526    4.52393  -36.48522  -70.97584 -102.95390
   5   83.74310   44.08476   -6.54743  -50.41028  -87.11562
   6  143.66660   89.90799   22.49734  -37.70668  -82.65437
   7  187.39134  142.05288   84.66171   34.21603   -5.80963
   8  196.90443  140.73220   70.44951    7.44831  -38.91027
   9  194.55254  114.45726   15.70761  -75.01861 -135.36147
  10  105.62394   12.32563 -102.13482 -208.16238 -276.22311

function g02zk_example
sorder = int64(1);
c1 = 'y';
weight = 'u';
dat = [ 420.1577;  541.4117;  901.1575;  639.0802;  750.8756;  945.7989;
        829.3979;  979.1648; 1309.8789; 1492.3987;  502.8390;  616.7168;
        790.9225;  555.8786;  713.4412;  838.7561;  535.0766;  596.4408;
        924.5619;  487.7583;  692.6397;  997.8770;  506.9995;  654.1587;
        933.9193;  433.6813;  587.5962;  896.4746;  454.4782;  584.9989;
        800.7990;  502.4369;  713.5197;  906.0006;  880.5969;  796.8289;
        854.8791; 1167.3716;  523.8000;  670.7792;  377.0584;  851.5430;
       1121.0937;  625.5179;  805.5377;  558.5812;  884.4005; 1257.4989;
       2051.1789; 1466.3330;  730.0989; 2432.3910;  940.9218; 1177.8547;
       1222.5939; 1519.5811;  687.6638;  953.1192;  953.1192;  953.1192;
        939.0418; 1283.4025; 1511.5789; 1342.5821;  511.7980;  689.7988;
       1532.3074; 1056.0808;  387.3195;  387.3195;  410.9987;  499.7510;
        832.7554;  614.9986;  887.4658; 1595.1611; 1807.9520;  541.2006;
       1057.6767;  800.7990; 1245.6964; 1201.0002;  634.4002;  956.2315;
       1148.6010; 1768.8236; 2822.5330;  922.3548; 2293.1920;  627.4726;
        889.9809; 1162.2000; 1197.0794;  530.7972; 1142.1526; 1088.0039;
        484.6612; 1536.0201;  678.8974;  671.8802;  690.4683;  860.6948;
        873.3095;  894.4598; 1148.6470;  926.8762;  839.0414;  829.4974;
       1264.0043; 1937.9771;  698.8317;  920.4199; 1897.5711;  891.6824;
        889.6784; 1221.4818;  544.5991; 1031.4491; 1462.9497;  830.4353;
        975.0415; 1337.9983;  867.6427;  725.7459;  989.0056; 1525.0005;
        672.1960;  923.3977;  472.3215;  590.7601;  831.7983; 1139.4945;
        507.5169;  576.1972;  696.5991;  650.8180;  949.5802;  497.1193;
        570.1674;  724.7306;  408.3399;  638.6713; 1225.7890;  715.3701;
        800.4708;  975.5974; 1613.7565;  608.5019;  958.6634;  835.9426;
       1024.8177; 1006.4353;  726.0000;  494.4174;  776.5958;  415.4407;
        581.3599;  643.3571; 2551.6615; 1795.3226; 1165.7734;  815.6212;
       1264.2066; 1095.4056;  447.4479; 1178.9742;  975.8023; 1017.8522;
        423.8798;  558.7767;  943.2487; 1348.3002; 2340.6174;  587.1792;
       1540.9741; 1115.8481; 1044.6843; 1389.7929; 2497.7860; 1585.3809;
       1862.0438; 2008.8546;  697.3099;  571.2517;  598.3465;  461.0977;
        977.1107;  883.9849;  718.3594;  543.8971; 1587.3480; 4957.8130;
        969.6838;  419.9980;  561.9990;  689.5988; 1398.5203;  820.8168;
        875.1716; 1392.4499; 1256.3174; 1362.8590; 1999.2552; 1209.4730;
       1125.0356; 1827.4010; 1014.1540;  880.3944;  873.7375;  951.4432;
        473.0022;  601.0030;  713.9979;  829.2984;  959.7953; 1212.9613;
        958.8743; 1129.4431; 1943.0419;  539.6388;  463.5990;  562.6400;
        736.7584; 1415.4461; 2208.7897;  636.0009;  759.4010; 1078.8382;
        748.6413;  987.6417;  788.0961; 1020.0225; 1230.9235;  440.5174;
        743.0772];
y = [ 255.8394;  310.9587;  485.6800;  402.9974;  495.5608;  633.7978;
      630.7566;  700.4409;  830.9586;  815.3602;  338.0014;  412.3613;
      520.0006;  452.4015;  512.7201;  658.8395;  392.5995;  443.5586;
      640.1164;  333.8394;  466.9583;  543.3969;  317.7198;  424.3209;
      518.9617;  338.0014;  419.6412;  476.3200;  386.3602;  423.2783;
      503.3572;  354.6389;  497.3182;  588.5195;  654.5971;  550.7274;
      528.3770;  640.4813;  401.3204;  435.9990;  276.5606;  588.3488;
      664.1978;  444.8602;  462.8995;  377.7792;  553.1504;  810.8962;
     1067.9541; 1049.8788;  522.7012; 1424.8047;  517.9196;  830.9586;
      925.5795; 1162.0024;  383.4580;  621.1173;  621.1173;  621.1173;
      548.6002;  745.2353;  837.8005;  795.3402;  418.5976;  508.7974;
      883.2780;  742.5276;  242.3202;  242.3202;  266.0010;  408.4992;
      614.7588;  385.3184;  515.6200; 1138.1620;  993.9630;  299.1993;
      750.3202;  572.0807;  907.3969;  811.5776;  427.7975;  649.9985;
      860.6002; 1143.4211; 2032.6792;  590.6183; 1570.3911;  483.4800;
      600.4804;  696.2021;  774.7962;  390.5984;  612.5619;  708.7622;
      296.9192; 1071.4627;  496.5976;  503.3974;  357.6411;  430.3376;
      624.6990;  582.5413;  580.2215;  543.8807;  588.6372;  627.9999;
      712.1012;  968.3949;  482.5816;  593.1694; 1033.5658;  693.6795;
      693.6795;  761.2791;  361.3981;  628.4522;  771.4486;  757.1187;
      821.5970; 1022.3202;  679.4407;  538.7491;  679.9981;  977.0033;
      561.2015;  728.3997;  372.3186;  361.5210;  620.8006;  819.9964;
      360.8780;  395.7608;  442.0001;  404.0384;  670.7993;  297.5702;
      353.4882;  383.9376;  284.8008;  431.1000;  801.3518;  448.4513;
      577.9111;  570.5210;  865.3205;  444.5578;  680.4198;  576.2779;
      708.4787;  734.2356;  433.0010;  327.4188;  485.5198;  305.4390;
      468.0008;  459.8177;  863.9199;  831.4407;  534.7610;  392.0502;
      934.9752;  813.3081;  263.7100;  769.0838;  630.5863;  645.9874;
      319.5584;  348.4518;  614.5068;  662.0096; 1504.3708;  406.2180;
      692.1689;  588.1371;  511.2609;  700.5600; 1301.1451;  879.0660;
      912.8851; 1509.7812;  484.0605;  399.6703;  444.1001;  248.8101;
      527.8014;  500.6313;  436.8107;  374.7990;  726.3921; 1827.2000;
      523.4911;  334.9998;  473.2009;  581.2029;  929.7540;  591.1974;
      637.5483;  674.9509;  776.7589;  959.5170; 1250.9643;  737.8201;
      810.6772;  983.0009;  708.8968;  633.1200;  631.7982;  608.6419;
      300.9999;  377.9984;  397.0015;  588.5195;  681.7616;  807.3603;
      696.8011;  811.1962; 1305.7201;  442.0001;  353.6013;  468.0008;
      526.7573;  890.2390; 1318.8033;  331.0005;  416.4015;  596.8406;
      429.0399;  619.6408;  400.7990;  775.0209;  772.7611;  306.5191;
      522.6019];
isx = [int64(1)];
tau = [0.10; 0.25; 0.50; 0.75; 0.90];
state = zeros(1, 1, 'int64');
ip = 2;
b = zeros(2, 5);
iopts = zeros(100, 1, 'int64');
opts = zeros(100, 1);
% Initialize the optional argument array
[iopts, opts, ifail] = g02zk('Initialize = g02qg', iopts, opts);

% Set optional arguments
[iopts, opts, ifail] = g02zk('Return Residuals = Yes', iopts, opts);
[iopts, opts, ifail] = g02zk('Matrix Returned = Covariance', iopts, opts);
[iopts, opts, ifail] = g02zk('Interval Method = IID', iopts, opts);

% Call the model fitting routine
[df, b, bl, bu, ch, res, state, info, ifail] = ...
    g02qg(sorder, c1, weight, dat, isx, y, tau, b, iopts, opts, state);

if (ifail == 0)
  % Display the parameter estimates
  for l=1:numel(tau)
    fprintf('\nQuantile: %6.3f\n\n', tau(l));
    fprintf('        Lower   Parameter   Upper\n');
    fprintf('        Limit   Estimate    Limit\n');
    for j=1:2
      fprintf('%3d   %7.3f   %7.3f   %7.3f\n', j, bl(j,l), b(j,l), bu(j,l));
    end
    fprintf('\nCovariance matrix\n');
    for i=1:ip
      fprintf('%10.3e ', ch(1:i, i, l));
      fprintf('\n');
    end
    fprintf('\n');
  end

  if (numel(res) > 0)
    fprintf('First 10 Residuals\n');
    fprintf('                              Quantile\n');
    fprintf('Obs.   %6.3f     %6.3f     %6.3f     %6.3f     %6.3f\n', tau);
    for i=1:10
      fprintf(' %3d %10.5f %10.5f %10.5f %10.5f %10.5f\n', i, res(i, 1:5));
    end
  else
    fprintf('Residuals not returned\n');
  end
elseif (ifail == 231)
  fprintf('\nAdditional error information (info):\n');
  disp(info);
end
 

Quantile:  0.100

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    74.946   110.142   145.337
  2     0.370     0.402     0.433

Covariance matrix
 3.191e+02 
-2.541e-01  2.587e-04 


Quantile:  0.250

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    64.232    95.483   126.735
  2     0.446     0.474     0.502

Covariance matrix
 2.516e+02 
-2.004e-01  2.039e-04 


Quantile:  0.500

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    55.399    81.482   107.566
  2     0.537     0.560     0.584

Covariance matrix
 1.753e+02 
-1.396e-01  1.421e-04 


Quantile:  0.750

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    41.372    62.396    83.421
  2     0.625     0.644     0.663

Covariance matrix
 1.139e+02 
-9.068e-02  9.230e-05 


Quantile:  0.900

        Lower   Parameter   Upper
        Limit   Estimate    Limit
  1    26.829    67.351   107.873
  2     0.650     0.686     0.723

Covariance matrix
 4.230e+02 
-3.369e-01  3.429e-04 

First 10 Residuals
                              Quantile
Obs.    0.100      0.250      0.500      0.750      0.900
   1  -23.10718  -38.84219  -61.00711  -77.14462  -99.86551
   2  -16.70358  -41.20981  -73.81193 -100.11463 -127.96277
   3   13.48419  -37.04518 -100.61322 -157.07478 -200.13481
   4   36.09526    4.52393  -36.48522  -70.97584 -102.95390
   5   83.74310   44.08476   -6.54743  -50.41028  -87.11562
   6  143.66660   89.90799   22.49734  -37.70668  -82.65437
   7  187.39134  142.05288   84.66171   34.21603   -5.80963
   8  196.90443  140.73220   70.44951    7.44831  -38.91027
   9  194.55254  114.45726   15.70761  -75.01861 -135.36147
  10  105.62394   12.32563 -102.13482 -208.16238 -276.22311


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Chapter Contents
Chapter Introduction
NAG Toolbox

© The Numerical Algorithms Group Ltd, Oxford, UK. 2009–2013