all.regs: Goodness of Fit Measures for a Regression Hierarchy
In hier.part: Hierarchical Partitioning
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
Calculates goodness of fit measures for regressions of a single
response variable to all combinations of N predictor variables
Usage
1
2
3
4
5
6
7
Arguments
y
a vector containing the response variable
xcan
a data.frame containing the n predictors
family
a character string naming a family function used by stats::glm
(See stats::family for details of family functions). Valid values
are "gaussian", "binomial", "Gamma", "inverse.gaussian", "poisson",
"quasi", "quasibinomial","quasipoisson". Alternatively a value of "beta"
will use the betareg::betareg beta regression model, or "ordinal"
will use the MASS::polr ordered logistic or probit regression.
For these last two options, a value for the link argument is required.
link
character specification of the link function, only used if family =
"beta" or "ordinal". For "beta", this argument equals the "link" argument
in betareg::betareg. For "ordinal", it equals the "method"
argument in MASS::polr, where "logit" = "logistic".
gof
Goodness-of-fit measure. Currently "RMSPE", Root-mean-square
'prediction' error, "logLik", Log-Likelihood or "Rsqu", R-squared.
R-squared is only applicable if family = "Gaussian".
print.vars
if FALSE, the function returns a vector of goodness-of-fit measures. If
TRUE, a data frame is returned with first column listing predictor variable
combinations and the second column listing goodness-of-fit measures.
...
additional arguments to passed to glm, betareg::betareg, or MASS::polr
Details
This function calculates goodness of fit measures for the entire
hierarchy of models using all combinations of N predictors, and
returns them as an ordered list ready for input into the function
partition.
Value
gfs
If print.vars is FALSE, a vector of goodness of fit measures for all
combinations of predictors in the hierarchy or, if
print.vars is TRUE, a data frame listing all combinations of
predictor variables in the first column in ascending order, and
the corresponding goodness of fit measure for the model using those
variables
Author(s)
Chris Walsh cwalsh@unimelb.edu.au.
References
Hatt, B. E., Fletcher, T. D., Walsh, C. J. and Taylor, S. L. 2004 The
influence of urban density and drainage infrastructure on the
concentrations and loads of pollutants in small
streams. Environmental Management 34, 112–124.
Walsh, C. J., Papas, P. J., Crowther, D., Sim, P. T., and Yoo, J. 2004
Stormwater drainage pipes as a threat to a stream-dwelling amphipod of
conservation significance, Austrogammarus australis, in southeastern
Australia. Biodiversity and Conservation 13, 781–793.
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
#linear regression of log(electrical conductivity) in streams
#against seven independent variables describing catchment
#characteristics (from Hatt et al. 2004).
data(urbanwq)
env <- urbanwq[,2:8]
all.regs(urbanwq$lec, env, fam = "gaussian", gof = "Rsqu",
print.vars = TRUE)
#logistic regression of an amphipod species occurrence in
#streams against four independent variables describing
#catchment characteristics (from Walsh et al. 2004).
data(amphipod)
env1 <- amphipod[,2:5]
all.regs(amphipod$australis, env1, fam = "binomial",
gof = "logLik", print.vars = TRUE)
Example output
Loading required package: gtools
regressions done: formatting results
variable.combination gof
1 Theta 0.00000000
2 fimp 0.59047318
3 sconn 0.82682075
4 sdensep 0.01098174
5 unsealden 0.39635905
6 fcarea 0.12282709
7 selev 0.62445471
8 amgeast 0.33033972
9 fimp sconn 0.83410378
10 fimp sdensep 0.59758915
11 fimp unsealden 0.62061433
12 fimp fcarea 0.65284362
13 fimp selev 0.77159448
14 fimp amgeast 0.60702109
15 sconn sdensep 0.82683793
16 sconn unsealden 0.82691037
17 sconn fcarea 0.83582029
18 sconn selev 0.85403927
19 sconn amgeast 0.84727070
20 sdensep unsealden 0.41798147
21 sdensep fcarea 0.13980912
22 sdensep selev 0.76026824
23 sdensep amgeast 0.33080645
24 unsealden fcarea 0.39744819
25 unsealden selev 0.66503431
26 unsealden amgeast 0.52650125
27 fcarea selev 0.67608730
28 fcarea amgeast 0.43330271
29 selev amgeast 0.64633406
30 fimp sconn sdensep 0.83447868
31 fimp sconn unsealden 0.83411192
32 fimp sconn fcarea 0.83965414
33 fimp sconn selev 0.85551898
34 fimp sconn amgeast 0.84727151
35 fimp sdensep unsealden 0.62061622
36 fimp sdensep fcarea 0.65949970
37 fimp sdensep selev 0.82672399
38 fimp sdensep amgeast 0.62672410
39 fimp unsealden fcarea 0.65445206
40 fimp unsealden selev 0.77226833
41 fimp unsealden amgeast 0.62512912
42 fimp fcarea selev 0.77811174
43 fimp fcarea amgeast 0.66312305
44 fimp selev amgeast 0.82026934
45 sconn sdensep unsealden 0.82691040
46 sconn sdensep fcarea 0.84141253
47 sconn sdensep selev 0.87751308
48 sconn sdensep amgeast 0.84785650
49 sconn unsealden fcarea 0.83932285
50 sconn unsealden selev 0.85513956
51 sconn unsealden amgeast 0.84985538
52 sconn fcarea selev 0.85490360
53 sconn fcarea amgeast 0.85107746
54 sconn selev amgeast 0.87685251
55 sdensep unsealden fcarea 0.43348171
56 sdensep unsealden selev 0.81801707
57 sdensep unsealden amgeast 0.55827372
58 sdensep fcarea selev 0.76851361
59 sdensep fcarea amgeast 0.50536622
60 sdensep selev amgeast 0.77107209
61 unsealden fcarea selev 0.73969961
62 unsealden fcarea amgeast 0.53654123
63 unsealden selev amgeast 0.68316625
64 fcarea selev amgeast 0.67713148
65 fimp sconn sdensep unsealden 0.83451931
66 fimp sconn sdensep fcarea 0.84541929
67 fimp sconn sdensep selev 0.87865868
68 fimp sconn sdensep amgeast 0.84793008
69 fimp sconn unsealden fcarea 0.84176310
70 fimp sconn unsealden selev 0.85633390
71 fimp sconn unsealden amgeast 0.85010056
72 fimp sconn fcarea selev 0.85662169
73 fimp sconn fcarea amgeast 0.85116200
74 fimp sconn selev amgeast 0.88236321
75 fimp sdensep unsealden fcarea 0.66297682
76 fimp sdensep unsealden selev 0.84039075
77 fimp sdensep unsealden amgeast 0.62908864
78 fimp sdensep fcarea selev 0.82701685
79 fimp sdensep fcarea amgeast 0.66414800
80 fimp sdensep selev amgeast 0.85116957
81 fimp unsealden fcarea selev 0.78348135
82 fimp unsealden fcarea amgeast 0.66312339
83 fimp unsealden selev amgeast 0.82956916
84 fimp fcarea selev amgeast 0.85200153
85 sconn sdensep unsealden fcarea 0.84338543
86 sconn sdensep unsealden selev 0.87900342
87 sconn sdensep unsealden amgeast 0.85317612
88 sconn sdensep fcarea selev 0.87755498
89 sconn sdensep fcarea amgeast 0.85162358
90 sconn sdensep selev amgeast 0.89200389
91 sconn unsealden fcarea selev 0.85535421
92 sconn unsealden fcarea amgeast 0.85816222
93 sconn unsealden selev amgeast 0.88318976
94 sconn fcarea selev amgeast 0.88611089
95 sdensep unsealden fcarea selev 0.83628377
96 sdensep unsealden fcarea amgeast 0.61132790
97 sdensep unsealden selev amgeast 0.82521005
98 sdensep fcarea selev amgeast 0.77285776
99 unsealden fcarea selev amgeast 0.74013871
100 fimp sconn sdensep unsealden fcarea 0.84631087
101 fimp sconn sdensep unsealden selev 0.88052535
102 fimp sconn sdensep unsealden amgeast 0.85779318
103 fimp sconn sdensep fcarea selev 0.87866729
104 fimp sconn sdensep fcarea amgeast 0.85162457
105 fimp sconn sdensep selev amgeast 0.89525987
106 fimp sconn unsealden fcarea selev 0.85679323
107 fimp sconn unsealden fcarea amgeast 0.86058475
108 fimp sconn unsealden selev amgeast 0.89708584
109 fimp sconn fcarea selev amgeast 0.89557323
110 fimp sdensep unsealden fcarea selev 0.84575908
111 fimp sdensep unsealden fcarea amgeast 0.66461591
112 fimp sdensep unsealden selev amgeast 0.85137732
113 fimp sdensep fcarea selev amgeast 0.86367597
114 fimp unsealden fcarea selev amgeast 0.85322499
115 sconn sdensep unsealden fcarea selev 0.87916623
116 sconn sdensep unsealden fcarea amgeast 0.85818567
117 sconn sdensep unsealden selev amgeast 0.89224695
118 sconn sdensep fcarea selev amgeast 0.89515882
119 sconn unsealden fcarea selev amgeast 0.88779139
120 sdensep unsealden fcarea selev amgeast 0.83642968
121 fimp sconn sdensep unsealden fcarea selev 0.88093891
122 fimp sconn sdensep unsealden fcarea amgeast 0.86223879
123 fimp sconn sdensep unsealden selev amgeast 0.89900950
124 fimp sconn sdensep fcarea selev amgeast 0.90101494
125 fimp sconn unsealden fcarea selev amgeast 0.90231612
126 fimp sdensep unsealden fcarea selev amgeast 0.86447417
127 sconn sdensep unsealden fcarea selev amgeast 0.89516613
128 fimp sconn sdensep unsealden fcarea selev amgeast 0.90324171
regressions done: formatting results
variable.combination gof
1 Theta -36.68245
2 fimp -30.29727
3 fconn -25.58116
4 densep -36.31127
5 unseal -31.24099
6 fimp fconn -25.53568
7 fimp densep -28.91701
8 fimp unseal -29.44569
9 fconn densep -24.13048
10 fconn unseal -25.02936
11 densep unseal -31.21361
12 fimp fconn densep -23.40491
13 fimp fconn unseal -24.66242
14 fimp densep unseal -28.49188
15 fconn densep unseal -23.40579
16 fimp fconn densep unseal -23.17074
hier.part documentation built on March 3, 2020, 9:07 a.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
Calculates goodness of fit measures for regressions of a single response variable to all combinations of N predictor variables
Usage
1 2 3 4 5 6 7 |
Arguments
y |
a vector containing the response variable |
xcan |
a data.frame containing the n predictors |
family |
a character string naming a family function used by |
link |
character specification of the link function, only used if family =
"beta" or "ordinal". For "beta", this argument equals the "link" argument
in |
gof |
Goodness-of-fit measure. Currently "RMSPE", Root-mean-square 'prediction' error, "logLik", Log-Likelihood or "Rsqu", R-squared. R-squared is only applicable if family = "Gaussian". |
print.vars |
if FALSE, the function returns a vector of goodness-of-fit measures. If TRUE, a data frame is returned with first column listing predictor variable combinations and the second column listing goodness-of-fit measures. |
... |
additional arguments to passed to |
Details
This function calculates goodness of fit measures for the entire
hierarchy of models using all combinations of N predictors, and
returns them as an ordered list ready for input into the function
partition.
Value
gfs |
If print.vars is FALSE, a vector of goodness of fit measures for all combinations of predictors in the hierarchy or, if print.vars is TRUE, a data frame listing all combinations of predictor variables in the first column in ascending order, and the corresponding goodness of fit measure for the model using those variables |
Author(s)
Chris Walsh cwalsh@unimelb.edu.au.
References
Hatt, B. E., Fletcher, T. D., Walsh, C. J. and Taylor, S. L. 2004 The influence of urban density and drainage infrastructure on the concentrations and loads of pollutants in small streams. Environmental Management 34, 112–124.
Walsh, C. J., Papas, P. J., Crowther, D., Sim, P. T., and Yoo, J. 2004 Stormwater drainage pipes as a threat to a stream-dwelling amphipod of conservation significance, Austrogammarus australis, in southeastern Australia. Biodiversity and Conservation 13, 781–793.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | #linear regression of log(electrical conductivity) in streams
#against seven independent variables describing catchment
#characteristics (from Hatt et al. 2004).
data(urbanwq)
env <- urbanwq[,2:8]
all.regs(urbanwq$lec, env, fam = "gaussian", gof = "Rsqu",
print.vars = TRUE)
#logistic regression of an amphipod species occurrence in
#streams against four independent variables describing
#catchment characteristics (from Walsh et al. 2004).
data(amphipod)
env1 <- amphipod[,2:5]
all.regs(amphipod$australis, env1, fam = "binomial",
gof = "logLik", print.vars = TRUE)
|
Example output
Loading required package: gtools
regressions done: formatting results
variable.combination gof
1 Theta 0.00000000
2 fimp 0.59047318
3 sconn 0.82682075
4 sdensep 0.01098174
5 unsealden 0.39635905
6 fcarea 0.12282709
7 selev 0.62445471
8 amgeast 0.33033972
9 fimp sconn 0.83410378
10 fimp sdensep 0.59758915
11 fimp unsealden 0.62061433
12 fimp fcarea 0.65284362
13 fimp selev 0.77159448
14 fimp amgeast 0.60702109
15 sconn sdensep 0.82683793
16 sconn unsealden 0.82691037
17 sconn fcarea 0.83582029
18 sconn selev 0.85403927
19 sconn amgeast 0.84727070
20 sdensep unsealden 0.41798147
21 sdensep fcarea 0.13980912
22 sdensep selev 0.76026824
23 sdensep amgeast 0.33080645
24 unsealden fcarea 0.39744819
25 unsealden selev 0.66503431
26 unsealden amgeast 0.52650125
27 fcarea selev 0.67608730
28 fcarea amgeast 0.43330271
29 selev amgeast 0.64633406
30 fimp sconn sdensep 0.83447868
31 fimp sconn unsealden 0.83411192
32 fimp sconn fcarea 0.83965414
33 fimp sconn selev 0.85551898
34 fimp sconn amgeast 0.84727151
35 fimp sdensep unsealden 0.62061622
36 fimp sdensep fcarea 0.65949970
37 fimp sdensep selev 0.82672399
38 fimp sdensep amgeast 0.62672410
39 fimp unsealden fcarea 0.65445206
40 fimp unsealden selev 0.77226833
41 fimp unsealden amgeast 0.62512912
42 fimp fcarea selev 0.77811174
43 fimp fcarea amgeast 0.66312305
44 fimp selev amgeast 0.82026934
45 sconn sdensep unsealden 0.82691040
46 sconn sdensep fcarea 0.84141253
47 sconn sdensep selev 0.87751308
48 sconn sdensep amgeast 0.84785650
49 sconn unsealden fcarea 0.83932285
50 sconn unsealden selev 0.85513956
51 sconn unsealden amgeast 0.84985538
52 sconn fcarea selev 0.85490360
53 sconn fcarea amgeast 0.85107746
54 sconn selev amgeast 0.87685251
55 sdensep unsealden fcarea 0.43348171
56 sdensep unsealden selev 0.81801707
57 sdensep unsealden amgeast 0.55827372
58 sdensep fcarea selev 0.76851361
59 sdensep fcarea amgeast 0.50536622
60 sdensep selev amgeast 0.77107209
61 unsealden fcarea selev 0.73969961
62 unsealden fcarea amgeast 0.53654123
63 unsealden selev amgeast 0.68316625
64 fcarea selev amgeast 0.67713148
65 fimp sconn sdensep unsealden 0.83451931
66 fimp sconn sdensep fcarea 0.84541929
67 fimp sconn sdensep selev 0.87865868
68 fimp sconn sdensep amgeast 0.84793008
69 fimp sconn unsealden fcarea 0.84176310
70 fimp sconn unsealden selev 0.85633390
71 fimp sconn unsealden amgeast 0.85010056
72 fimp sconn fcarea selev 0.85662169
73 fimp sconn fcarea amgeast 0.85116200
74 fimp sconn selev amgeast 0.88236321
75 fimp sdensep unsealden fcarea 0.66297682
76 fimp sdensep unsealden selev 0.84039075
77 fimp sdensep unsealden amgeast 0.62908864
78 fimp sdensep fcarea selev 0.82701685
79 fimp sdensep fcarea amgeast 0.66414800
80 fimp sdensep selev amgeast 0.85116957
81 fimp unsealden fcarea selev 0.78348135
82 fimp unsealden fcarea amgeast 0.66312339
83 fimp unsealden selev amgeast 0.82956916
84 fimp fcarea selev amgeast 0.85200153
85 sconn sdensep unsealden fcarea 0.84338543
86 sconn sdensep unsealden selev 0.87900342
87 sconn sdensep unsealden amgeast 0.85317612
88 sconn sdensep fcarea selev 0.87755498
89 sconn sdensep fcarea amgeast 0.85162358
90 sconn sdensep selev amgeast 0.89200389
91 sconn unsealden fcarea selev 0.85535421
92 sconn unsealden fcarea amgeast 0.85816222
93 sconn unsealden selev amgeast 0.88318976
94 sconn fcarea selev amgeast 0.88611089
95 sdensep unsealden fcarea selev 0.83628377
96 sdensep unsealden fcarea amgeast 0.61132790
97 sdensep unsealden selev amgeast 0.82521005
98 sdensep fcarea selev amgeast 0.77285776
99 unsealden fcarea selev amgeast 0.74013871
100 fimp sconn sdensep unsealden fcarea 0.84631087
101 fimp sconn sdensep unsealden selev 0.88052535
102 fimp sconn sdensep unsealden amgeast 0.85779318
103 fimp sconn sdensep fcarea selev 0.87866729
104 fimp sconn sdensep fcarea amgeast 0.85162457
105 fimp sconn sdensep selev amgeast 0.89525987
106 fimp sconn unsealden fcarea selev 0.85679323
107 fimp sconn unsealden fcarea amgeast 0.86058475
108 fimp sconn unsealden selev amgeast 0.89708584
109 fimp sconn fcarea selev amgeast 0.89557323
110 fimp sdensep unsealden fcarea selev 0.84575908
111 fimp sdensep unsealden fcarea amgeast 0.66461591
112 fimp sdensep unsealden selev amgeast 0.85137732
113 fimp sdensep fcarea selev amgeast 0.86367597
114 fimp unsealden fcarea selev amgeast 0.85322499
115 sconn sdensep unsealden fcarea selev 0.87916623
116 sconn sdensep unsealden fcarea amgeast 0.85818567
117 sconn sdensep unsealden selev amgeast 0.89224695
118 sconn sdensep fcarea selev amgeast 0.89515882
119 sconn unsealden fcarea selev amgeast 0.88779139
120 sdensep unsealden fcarea selev amgeast 0.83642968
121 fimp sconn sdensep unsealden fcarea selev 0.88093891
122 fimp sconn sdensep unsealden fcarea amgeast 0.86223879
123 fimp sconn sdensep unsealden selev amgeast 0.89900950
124 fimp sconn sdensep fcarea selev amgeast 0.90101494
125 fimp sconn unsealden fcarea selev amgeast 0.90231612
126 fimp sdensep unsealden fcarea selev amgeast 0.86447417
127 sconn sdensep unsealden fcarea selev amgeast 0.89516613
128 fimp sconn sdensep unsealden fcarea selev amgeast 0.90324171
regressions done: formatting results
variable.combination gof
1 Theta -36.68245
2 fimp -30.29727
3 fconn -25.58116
4 densep -36.31127
5 unseal -31.24099
6 fimp fconn -25.53568
7 fimp densep -28.91701
8 fimp unseal -29.44569
9 fconn densep -24.13048
10 fconn unseal -25.02936
11 densep unseal -31.21361
12 fimp fconn densep -23.40491
13 fimp fconn unseal -24.66242
14 fimp densep unseal -28.49188
15 fconn densep unseal -23.40579
16 fimp fconn densep unseal -23.17074
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