From c322a8102a399cbb1fe38c4c4ca4485cea8bc4e8 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 7 May 2019 08:43:12 +0200 Subject: Fix hessian calculations Static documentation rebuilt by pkgdown --- docs/reference/mkinfit.html | 176 ++++++++++++++++++++++++++------------------ 1 file changed, 104 insertions(+), 72 deletions(-) (limited to 'docs/reference/mkinfit.html') diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index b75b7c95..09329a86 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -360,17 +360,17 @@ Per default, parameters in the kinetic models are internally transformed in

Examples

# Use shorthand notation for parent only degradation
 fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-summary(fit)
#> Warning: Could not calculate correlation; no covariance matrix
#> mkin version used for fitting:    0.9.49.4 
+summary(fit)
#> mkin version used for fitting:    0.9.49.4 
 #> R version used for fitting:       3.6.0 
-#> Date of fit:     Tue May  7 08:08:23 2019 
-#> Date of summary: Tue May  7 08:08:23 2019 
+#> Date of fit:     Tue May  7 08:36:16 2019 
+#> Date of summary: Tue May  7 08:36:16 2019 
 #> 
 #> Equations:
 #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted using 66 model solutions performed in 0.139 s
+#> Fitted using 222 model solutions performed in 0.89 s
 #> 
 #> Error model:
 #> Constant variance 
@@ -393,23 +393,28 @@ Per default, parameters in the kinetic models are internally transformed in
 #> None
 #> 
 #> Optimised, transformed parameters with symmetric confidence intervals:
-#>           Estimate Std. Error Lower Upper
-#> parent_0  85.87000         NA    NA    NA
-#> log_alpha  0.05192         NA    NA    NA
-#> log_beta   0.65100         NA    NA    NA
-#> sigma      1.85700         NA    NA    NA
+#>           Estimate Std. Error    Lower   Upper
+#> parent_0  85.87000     1.8070 81.23000 90.5200
+#> log_alpha  0.05192     0.1353 -0.29580  0.3996
+#> log_beta   0.65100     0.2287  0.06315  1.2390
+#> sigma      1.85700     0.4378  0.73200  2.9830
 #> 
 #> Parameter correlation:
-#> No covariance matrix
+#>             parent_0  log_alpha   log_beta     sigma
+#> parent_0   1.000e+00 -1.565e-01 -3.142e-01 4.770e-08
+#> log_alpha -1.565e-01  1.000e+00  9.564e-01 9.974e-08
+#> log_beta  -3.142e-01  9.564e-01  1.000e+00 8.468e-08
+#> sigma      4.770e-08  9.974e-08  8.468e-08 1.000e+00
+#> 
 #> Backtransformed parameters:
 #> Confidence intervals for internally transformed parameters are asymmetric.
 #> t-test (unrealistically) based on the assumption of normal distribution
 #> for estimators of untransformed parameters.
-#>          Estimate t value Pr(>t) Lower Upper
-#> parent_0   85.870      NA     NA    NA    NA
-#> alpha       1.053      NA     NA    NA    NA
-#> beta        1.917      NA     NA    NA    NA
-#> sigma       1.857      NA     NA    NA    NA
+#>          Estimate t value    Pr(>t)   Lower  Upper
+#> parent_0   85.870  47.530 3.893e-08 81.2300 90.520
+#> alpha       1.053   7.393 3.562e-04  0.7439  1.491
+#> beta        1.917   4.373 3.601e-03  1.0650  3.451
+#> sigma       1.857   4.243 4.074e-03  0.7320  2.983
 #> 
 #> FOCUS Chi2 error levels in percent:
 #>          err.min n.optim df
@@ -438,7 +443,7 @@ Per default, parameters in the kinetic models are internally transformed in
   m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
 print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
                            solution_type = "eigen", quiet = TRUE)))
#> Warning: Observations with value of zero were removed from the data
#>        User      System verstrichen 
-#>       0.637       0.000       0.640 
coef(fit)
#> NULL
endpoints(fit)
#> $ff
+#>       2.251       0.000       2.253 
coef(fit)
#> NULL
endpoints(fit)
#> $ff
 #> parent_sink   parent_m1     m1_sink 
 #>    0.485524    0.514476    1.000000 
 #> 
@@ -510,7 +515,7 @@ Per default, parameters in the kinetic models are internally transformed in
 #> Sum of squared residuals at call 126: 371.2134
 #> Sum of squared residuals at call 135: 371.2134
 #> Negative log-likelihood at call 145: 97.22429
#> Optimisation successfully terminated.
#>        User      System verstrichen 
-#>       0.544       0.000       0.550 
coef(fit.deSolve)
#> NULL
endpoints(fit.deSolve)
#> $ff
+#>       1.151       0.000       1.152 
coef(fit.deSolve)
#> NULL
endpoints(fit.deSolve)
#> $ff
 #> parent_sink   parent_m1     m1_sink 
 #>    0.485524    0.514476    1.000000 
 #> 
@@ -540,10 +545,10 @@ Per default, parameters in the kinetic models are internally transformed in
 fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data

 
# Weighted fits, including IRLS
 SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"),
-                      m1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.noweight)
#> Warning: Could not calculate correlation; no covariance matrix
#> mkin version used for fitting:    0.9.49.4 
+                      m1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.noweight)
#> mkin version used for fitting:    0.9.49.4 
 #> R version used for fitting:       3.6.0 
-#> Date of fit:     Tue May  7 08:08:30 2019 
-#> Date of summary: Tue May  7 08:08:30 2019 
+#> Date of fit:     Tue May  7 08:36:33 2019 
+#> Date of summary: Tue May  7 08:36:33 2019 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent * parent
@@ -551,7 +556,7 @@ Per default, parameters in the kinetic models are internally transformed in
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted using 185 model solutions performed in 0.499 s
+#> Fitted using 421 model solutions performed in 1.1 s
 #> 
 #> Error model:
 #> Constant variance 
@@ -577,25 +582,31 @@ Per default, parameters in the kinetic models are internally transformed in
 #> m1_0     0 state
 #> 
 #> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error Lower Upper
-#> parent_0       99.60000         NA    NA    NA
-#> log_k_parent   -2.31600         NA    NA    NA
-#> log_k_m1       -5.24800         NA    NA    NA
-#> f_parent_ilr_1  0.04096         NA    NA    NA
-#> sigma           3.12600         NA    NA    NA
+#>                Estimate Std. Error    Lower    Upper
+#> parent_0       99.60000    1.57000 96.40000 102.8000
+#> log_k_parent   -2.31600    0.04087 -2.39900  -2.2330
+#> log_k_m1       -5.24800    0.13320 -5.51800  -4.9770
+#> f_parent_ilr_1  0.04096    0.06312 -0.08746   0.1694
+#> sigma           3.12600    0.35850  2.39600   3.8550
 #> 
 #> Parameter correlation:
-#> No covariance matrix
+#>                  parent_0 log_k_parent   log_k_m1 f_parent_ilr_1      sigma
+#> parent_0        1.000e+00    5.174e-01 -1.688e-01     -5.471e-01 -2.265e-07
+#> log_k_parent    5.174e-01    1.000e+00 -3.263e-01     -5.426e-01  3.785e-07
+#> log_k_m1       -1.688e-01   -3.263e-01  1.000e+00      7.478e-01 -1.386e-07
+#> f_parent_ilr_1 -5.471e-01   -5.426e-01  7.478e-01      1.000e+00 -3.641e-08
+#> sigma          -2.265e-07    3.785e-07 -1.386e-07     -3.641e-08  1.000e+00
+#> 
 #> Backtransformed parameters:
 #> Confidence intervals for internally transformed parameters are asymmetric.
 #> t-test (unrealistically) based on the assumption of normal distribution
 #> for estimators of untransformed parameters.
-#>                 Estimate t value Pr(>t) Lower Upper
-#> parent_0       99.600000      NA     NA    NA    NA
-#> k_parent        0.098700      NA     NA    NA    NA
-#> k_m1            0.005261      NA     NA    NA    NA
-#> f_parent_to_m1  0.514500      NA     NA    NA    NA
-#> sigma           3.126000      NA     NA    NA    NA
+#>                 Estimate t value    Pr(>t)     Lower     Upper
+#> parent_0       99.600000  63.430 2.298e-36 96.400000 1.028e+02
+#> k_parent        0.098700  24.470 4.955e-23  0.090820 1.073e-01
+#> k_m1            0.005261   7.510 6.165e-09  0.004012 6.898e-03
+#> f_parent_to_m1  0.514500  23.070 3.104e-22  0.469100 5.596e-01
+#> sigma           3.126000   8.718 2.235e-10  2.396000 3.855e+00
 #> 
 #> FOCUS Chi2 error levels in percent:
 #>          err.min n.optim df
@@ -652,10 +663,10 @@ Per default, parameters in the kinetic models are internally transformed in
 #>   100       m1    31.04  31.98163 -9.416e-01
 #>   100       m1    33.13  31.98163  1.148e+00
 #>   120       m1    25.15  28.78984 -3.640e+00
-#>   120       m1    33.31  28.78984  4.520e+00
f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.obs)
#> Warning: Could not calculate correlation; no covariance matrix
#> mkin version used for fitting:    0.9.49.4 
+#>   120       m1    33.31  28.78984  4.520e+00
f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.obs)
#> mkin version used for fitting:    0.9.49.4 
 #> R version used for fitting:       3.6.0 
-#> Date of fit:     Tue May  7 08:08:32 2019 
-#> Date of summary: Tue May  7 08:08:32 2019 
+#> Date of fit:     Tue May  7 08:36:35 2019 
+#> Date of summary: Tue May  7 08:36:35 2019 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent * parent
@@ -663,7 +674,7 @@ Per default, parameters in the kinetic models are internally transformed in
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted using 426 model solutions performed in 1.139 s
+#> Fitted using 758 model solutions performed in 1.991 s
 #> 
 #> Error model:
 #> Variance unique to each observed variable 
@@ -691,27 +702,41 @@ Per default, parameters in the kinetic models are internally transformed in
 #> m1_0     0 state
 #> 
 #> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error Lower Upper
-#> parent_0       99.65000         NA    NA    NA
-#> log_k_parent   -2.31300         NA    NA    NA
-#> log_k_m1       -5.25000         NA    NA    NA
-#> f_parent_ilr_1  0.03861         NA    NA    NA
-#> sigma_parent    3.40100         NA    NA    NA
-#> sigma_m1        2.85500         NA    NA    NA
+#>                Estimate Std. Error    Lower    Upper
+#> parent_0       99.65000    1.70200 96.19000 103.1000
+#> log_k_parent   -2.31300    0.04376 -2.40200  -2.2240
+#> log_k_m1       -5.25000    0.12430 -5.50400  -4.9970
+#> f_parent_ilr_1  0.03861    0.06171 -0.08708   0.1643
+#> sigma_parent    3.40100    0.56820  2.24400   4.5590
+#> sigma_m1        2.85500    0.45240  1.93400   3.7770
 #> 
 #> Parameter correlation:
-#> No covariance matrix
+#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1 sigma_parent
+#> parent_0        1.00000      0.51078 -0.19133       -0.59997     0.035670
+#> log_k_parent    0.51078      1.00000 -0.37458       -0.59239     0.069833
+#> log_k_m1       -0.19133     -0.37458  1.00000        0.74398    -0.026158
+#> f_parent_ilr_1 -0.59997     -0.59239  0.74398        1.00000    -0.041368
+#> sigma_parent    0.03567      0.06983 -0.02616       -0.04137     1.000000
+#> sigma_m1       -0.03385     -0.06627  0.02482        0.03925    -0.004628
+#>                 sigma_m1
+#> parent_0       -0.033847
+#> log_k_parent   -0.066265
+#> log_k_m1        0.024821
+#> f_parent_ilr_1  0.039255
+#> sigma_parent   -0.004628
+#> sigma_m1        1.000000
+#> 
 #> Backtransformed parameters:
 #> Confidence intervals for internally transformed parameters are asymmetric.
 #> t-test (unrealistically) based on the assumption of normal distribution
 #> for estimators of untransformed parameters.
-#>                 Estimate t value Pr(>t) Lower Upper
-#> parent_0       99.650000      NA     NA    NA    NA
-#> k_parent        0.098970      NA     NA    NA    NA
-#> k_m1            0.005245      NA     NA    NA    NA
-#> f_parent_to_m1  0.513600      NA     NA    NA    NA
-#> sigma_parent    3.401000      NA     NA    NA    NA
-#> sigma_m1        2.855000      NA     NA    NA    NA
+#>                 Estimate t value    Pr(>t)     Lower     Upper
+#> parent_0       99.650000  58.560 2.004e-34 96.190000 1.031e+02
+#> k_parent        0.098970  22.850 1.099e-21  0.090530 1.082e-01
+#> k_m1            0.005245   8.046 1.732e-09  0.004072 6.756e-03
+#> f_parent_to_m1  0.513600  23.560 4.352e-22  0.469300 5.578e-01
+#> sigma_parent    3.401000   5.985 5.662e-07  2.244000 4.559e+00
+#> sigma_m1        2.855000   6.311 2.215e-07  1.934000 3.777e+00
 #> 
 #> FOCUS Chi2 error levels in percent:
 #>          err.min n.optim df
@@ -768,10 +793,10 @@ Per default, parameters in the kinetic models are internally transformed in
 #>   100       m1    31.04  31.98774 -9.477e-01
 #>   100       m1    33.13  31.98774  1.142e+00
 #>   120       m1    25.15  28.80430 -3.654e+00
-#>   120       m1    33.31  28.80430  4.506e+00
f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.tc)
#> Warning: Could not calculate correlation; no covariance matrix
#> mkin version used for fitting:    0.9.49.4 
+#>   120       m1    33.31  28.80430  4.506e+00
f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
summary(f.tc)
#> mkin version used for fitting:    0.9.49.4 
 #> R version used for fitting:       3.6.0 
-#> Date of fit:     Tue May  7 08:08:34 2019 
-#> Date of summary: Tue May  7 08:08:34 2019 
+#> Date of fit:     Tue May  7 08:36:39 2019 
+#> Date of summary: Tue May  7 08:36:39 2019 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent * parent
@@ -779,7 +804,7 @@ Per default, parameters in the kinetic models are internally transformed in
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted using 489 model solutions performed in 2.013 s
+#> Fitted using 821 model solutions performed in 3.304 s
 #> 
 #> Error model:
 #> Two-component variance function 
@@ -807,27 +832,34 @@ Per default, parameters in the kinetic models are internally transformed in
 #> m1_0     0 state
 #> 
 #> Optimised, transformed parameters with symmetric confidence intervals:
-#>                 Estimate Std. Error Lower Upper
-#> parent_0       100.70000         NA    NA    NA
-#> log_k_parent    -2.29700         NA    NA    NA
-#> log_k_m1        -5.26600         NA    NA    NA
-#> f_parent_ilr_1   0.02374         NA    NA    NA
-#> sigma_low        0.00305         NA    NA    NA
-#> rsd_high         0.07928         NA    NA    NA
+#>                 Estimate Std. Error     Lower     Upper
+#> parent_0       100.70000   2.621000 95.400000 106.10000
+#> log_k_parent    -2.29700   0.008862 -2.315000  -2.27900
+#> log_k_m1        -5.26600   0.091310 -5.452000  -5.08000
+#> f_parent_ilr_1   0.02374   0.055300 -0.088900   0.13640
+#> sigma_low        0.00305   0.004829 -0.006786   0.01289
+#> rsd_high         0.07928   0.009418  0.060100   0.09847
 #> 
 #> Parameter correlation:
-#> No covariance matrix
+#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1 sigma_low rsd_high
+#> parent_0        1.00000      0.67644 -0.10215       -0.76822   0.14294 -0.08783
+#> log_k_parent    0.67644      1.00000 -0.15102       -0.59491   0.34611 -0.08125
+#> log_k_m1       -0.10215     -0.15102  1.00000        0.51808  -0.05236  0.01240
+#> f_parent_ilr_1 -0.76822     -0.59491  0.51808        1.00000  -0.13900  0.03248
+#> sigma_low       0.14294      0.34611 -0.05236       -0.13900   1.00000 -0.16546
+#> rsd_high       -0.08783     -0.08125  0.01240        0.03248  -0.16546  1.00000
+#> 
 #> Backtransformed parameters:
 #> Confidence intervals for internally transformed parameters are asymmetric.
 #> t-test (unrealistically) based on the assumption of normal distribution
 #> for estimators of untransformed parameters.
-#>                 Estimate t value Pr(>t) Lower Upper
-#> parent_0       1.007e+02      NA     NA    NA    NA
-#> k_parent       1.006e-01      NA     NA    NA    NA
-#> k_m1           5.167e-03      NA     NA    NA    NA
-#> f_parent_to_m1 5.084e-01      NA     NA    NA    NA
-#> sigma_low      3.050e-03      NA     NA    NA    NA
-#> rsd_high       7.928e-02      NA     NA    NA    NA
+#>                 Estimate  t value    Pr(>t)     Lower     Upper
+#> parent_0       1.007e+02  38.4300 1.180e-28 95.400000 1.061e+02
+#> k_parent       1.006e-01 112.8000 1.718e-43  0.098760 1.024e-01
+#> k_m1           5.167e-03  10.9500 1.172e-12  0.004290 6.223e-03
+#> f_parent_to_m1 5.084e-01  26.0100 2.146e-23  0.468600 5.481e-01
+#> sigma_low      3.050e-03   0.6314 2.661e-01 -0.006786 1.289e-02
+#> rsd_high       7.928e-02   8.4170 6.418e-10  0.060100 9.847e-02
 #> 
 #> FOCUS Chi2 error levels in percent:
 #>          err.min n.optim df
-- 
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