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tests/testthat/_snaps/methods.md
In PAGFL: Joint Estimation of Latent Groups and Group-Specific Coefficients in Panel Data Models
S3 pagfl
Groups: 3
Call:
pagfl(formula = y ~ a + b, data = data, n_periods = 150, lambda = 5)
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Call:
pagfl(formula = y ~ a + b, data = data, n_periods = 150, lambda = 5)
Balanced panel: N = 20, T = 150, obs = 3000
Convergence reached:
TRUE (542 iterations)
Information criterion:
IC lambda
1.04519 5.00000
Residuals:
Min 1Q Median 3Q Max
-3.10271 -0.67485 -0.01057 0.68122 3.23017
3 groups:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 1 1 2 1 1 2 2 2 3 3 2 3 1 3 3 3 1 2 2
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Residual standard error: 0.99552 on 2978 degrees of freedom
Mean squared error: 0.9838
Multiple R-squared: 0.91956, Adjusted R-squared: 0.91899
Code
summary(estim)
Output
Call:
pagfl(formula = y ~ a + b, data = data, index = c("i_index",
"t_index"), lambda = 1000)
Unbalanced panel: N = 20, T = 149-150, obs = 2998
Convergence reached:
TRUE (25 iterations)
Information criterion:
IC lambda
7.53725 1000.00000
Residuals:
Min 1Q Median 3Q Max
-10.62978 -1.66933 0.04107 1.65432 12.33992
1 group
Coefficients:
a b
Group 1 -2.08433 0.67843
Residual standard error: 2.75179 on 2976 degrees of freedom
Mean squared error: 7.51678
Multiple R-squared: 0.38579, Adjusted R-squared: 0.38146
S3 grouped_plm
Groups: 3
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = groups_0,
n_periods = 150)
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = groups_0,
n_periods = 150)
Balanced panel: N = 20, T = 150, obs = 3000
Information criterion: 1.04519
Residuals:
Min 1Q Median 3Q Max
-3.10271 -0.67485 -0.01057 0.68122 3.23017
3 groups:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 1 1 2 1 1 2 2 2 3 3 2 3 1 3 3 3 1 2 2
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Residual standard error: 0.99552 on 2978 degrees of freedom
Mean squared error: 0.9838
Multiple R-squared: 0.91956, Adjusted R-squared: 0.91899
Code
summary(estim)
Output
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = rep(1,
length(groups_0)), index = c("i_index", "t_index"))
Unbalanced panel: N = 20, T = 149-150, obs = 2998
Information criterion: 7.53725
Residuals:
Min 1Q Median 3Q Max
-10.62978 -1.66933 0.04107 1.65432 12.33992
1 group
Coefficients:
a b
Group 1 -2.08433 0.67843
Residual standard error: 2.75179 on 2976 degrees of freedom
Mean squared error: 7.51678
Multiple R-squared: 0.38579, Adjusted R-squared: 0.38146
S3 tv_pagfl
Code
estim
Output
Groups: 5
Call:
tv_pagfl(formula = y ~ X1, data = data, n_periods = 100, lambda = 7)
Call:
tv_pagfl(formula = y ~ X1, data = data, n_periods = 100, lambda = 7)
Balanced panel: N = 10, T = 100, obs = 1000
Convergence reached:
TRUE (1546 iterations)
Information criterion:
IC lambda
0.46339 7.00000
Residuals:
Min 1Q Median 3Q Max
-3.16362 -0.65668 -0.00871 0.72063 2.79348
5 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 4 5 5 3 5 3
Residual standard error: 1.02363 on 980 degrees of freedom
Mean squared error: 1.02686
Multiple R-squared: 0.81416, Adjusted R-squared: 0.81055
S3 grouped_tv_plm
Code
estim
Output
Groups: 3
Call:
grouped_tv_plm(formula = y ~ X1, data = data, groups = groups_0,
n_periods = 100)
Call:
grouped_tv_plm(formula = y ~ X1, data = data, groups = groups_0,
n_periods = 100)
Balanced panel: N = 10, T = 100, obs = 1000
Information criterion: 0.31399
Residuals:
Min 1Q Median 3Q Max
-3.52289 -0.64434 -0.01226 0.70892 2.87440
3 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 1 2 2 3 2 3
Residual standard error: 1.03669 on 980 degrees of freedom
Mean squared error: 1.05323
Multiple R-squared: 0.80939, Adjusted R-squared: 0.80569
S3 tv_pagfl const coef unbalanced
Call:
tv_pagfl(formula = y ~ X + a, data = df, index = c("i_index",
"t_index"), lambda = 25, const_coef = "a")
Unbalanced panel: N = 10, T = 66-77, obs = 710
Convergence reached:
TRUE (522 iterations)
Information criterion:
IC lambda
0.27202 25.00000
Residuals:
Min 1Q Median 3Q Max
-3.51599 -0.64003 0.03732 0.64440 2.96996
2 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 1 1 2 2 1 2 1
Constant coefficients:
a
Group 1 0.04494
Group 2 -0.06506
Residual standard error: 1.05644 on 689 degrees of freedom
Mean squared error: 1.08306
Multiple R-squared: 0.79851, Adjusted R-squared: 0.79266
Code
estim
Output
Groups: 2
Call:
tv_pagfl(formula = y ~ X + a, data = df, index = c("i_index",
"t_index"), lambda = 25, const_coef = "a")
S3 grouped_tv_plm const coef unbalanced summary
Call:
grouped_tv_plm(formula = y ~ X + a, data = df, groups = groups_0,
index = c("i_index", "t_index"), const_coef = "a")
Unbalanced panel: N = 10, T = 66-77, obs = 710
Information criterion: 0.28854
Residuals:
Min 1Q Median 3Q Max
-2.85704 -0.63292 0.01668 0.64120 2.77544
3 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 1 2 2 3 2 3
Constant coefficients:
a
Group 1 -0.02146
Group 2 -0.06506
Group 3 0.12088
Residual standard error: 1.01522 on 689 degrees of freedom
Mean squared error: 1.00019
Multiple R-squared: 0.81393, Adjusted R-squared: 0.80853
Code
estim
Output
Groups: 3
Call:
grouped_tv_plm(formula = y ~ X + a, data = df, groups = groups_0,
index = c("i_index", "t_index"), const_coef = "a")
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S3 pagfl
Groups: 3
Call:
pagfl(formula = y ~ a + b, data = data, n_periods = 150, lambda = 5)
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Call:
pagfl(formula = y ~ a + b, data = data, n_periods = 150, lambda = 5)
Balanced panel: N = 20, T = 150, obs = 3000
Convergence reached:
TRUE (542 iterations)
Information criterion:
IC lambda
1.04519 5.00000
Residuals:
Min 1Q Median 3Q Max
-3.10271 -0.67485 -0.01057 0.68122 3.23017
3 groups:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 1 1 2 1 1 2 2 2 3 3 2 3 1 3 3 3 1 2 2
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Residual standard error: 0.99552 on 2978 degrees of freedom
Mean squared error: 0.9838
Multiple R-squared: 0.91956, Adjusted R-squared: 0.91899
Code
summary(estim)
Output
Call:
pagfl(formula = y ~ a + b, data = data, index = c("i_index",
"t_index"), lambda = 1000)
Unbalanced panel: N = 20, T = 149-150, obs = 2998
Convergence reached:
TRUE (25 iterations)
Information criterion:
IC lambda
7.53725 1000.00000
Residuals:
Min 1Q Median 3Q Max
-10.62978 -1.66933 0.04107 1.65432 12.33992
1 group
Coefficients:
a b
Group 1 -2.08433 0.67843
Residual standard error: 2.75179 on 2976 degrees of freedom
Mean squared error: 7.51678
Multiple R-squared: 0.38579, Adjusted R-squared: 0.38146
S3 grouped_plm
Groups: 3
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = groups_0,
n_periods = 150)
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = groups_0,
n_periods = 150)
Balanced panel: N = 20, T = 150, obs = 3000
Information criterion: 1.04519
Residuals:
Min 1Q Median 3Q Max
-3.10271 -0.67485 -0.01057 0.68122 3.23017
3 groups:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 1 1 2 1 1 2 2 2 3 3 2 3 1 3 3 3 1 2 2
Coefficients:
a b
Group 1 -0.98847 1.54126
Group 2 -5.05014 -1.02301
Group 3 0.22479 1.54219
Residual standard error: 0.99552 on 2978 degrees of freedom
Mean squared error: 0.9838
Multiple R-squared: 0.91956, Adjusted R-squared: 0.91899
Code
summary(estim)
Output
Call:
grouped_plm(formula = y ~ a + b, data = data, groups = rep(1,
length(groups_0)), index = c("i_index", "t_index"))
Unbalanced panel: N = 20, T = 149-150, obs = 2998
Information criterion: 7.53725
Residuals:
Min 1Q Median 3Q Max
-10.62978 -1.66933 0.04107 1.65432 12.33992
1 group
Coefficients:
a b
Group 1 -2.08433 0.67843
Residual standard error: 2.75179 on 2976 degrees of freedom
Mean squared error: 7.51678
Multiple R-squared: 0.38579, Adjusted R-squared: 0.38146
S3 tv_pagfl
Code
estim
Output
Groups: 5
Call:
tv_pagfl(formula = y ~ X1, data = data, n_periods = 100, lambda = 7)
Call:
tv_pagfl(formula = y ~ X1, data = data, n_periods = 100, lambda = 7)
Balanced panel: N = 10, T = 100, obs = 1000
Convergence reached:
TRUE (1546 iterations)
Information criterion:
IC lambda
0.46339 7.00000
Residuals:
Min 1Q Median 3Q Max
-3.16362 -0.65668 -0.00871 0.72063 2.79348
5 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 4 5 5 3 5 3
Residual standard error: 1.02363 on 980 degrees of freedom
Mean squared error: 1.02686
Multiple R-squared: 0.81416, Adjusted R-squared: 0.81055
S3 grouped_tv_plm
Code
estim
Output
Groups: 3
Call:
grouped_tv_plm(formula = y ~ X1, data = data, groups = groups_0,
n_periods = 100)
Call:
grouped_tv_plm(formula = y ~ X1, data = data, groups = groups_0,
n_periods = 100)
Balanced panel: N = 10, T = 100, obs = 1000
Information criterion: 0.31399
Residuals:
Min 1Q Median 3Q Max
-3.52289 -0.64434 -0.01226 0.70892 2.87440
3 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 1 2 2 3 2 3
Residual standard error: 1.03669 on 980 degrees of freedom
Mean squared error: 1.05323
Multiple R-squared: 0.80939, Adjusted R-squared: 0.80569
S3 tv_pagfl const coef unbalanced
Call:
tv_pagfl(formula = y ~ X + a, data = df, index = c("i_index",
"t_index"), lambda = 25, const_coef = "a")
Unbalanced panel: N = 10, T = 66-77, obs = 710
Convergence reached:
TRUE (522 iterations)
Information criterion:
IC lambda
0.27202 25.00000
Residuals:
Min 1Q Median 3Q Max
-3.51599 -0.64003 0.03732 0.64440 2.96996
2 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 1 1 2 2 1 2 1
Constant coefficients:
a
Group 1 0.04494
Group 2 -0.06506
Residual standard error: 1.05644 on 689 degrees of freedom
Mean squared error: 1.08306
Multiple R-squared: 0.79851, Adjusted R-squared: 0.79266
Code
estim
Output
Groups: 2
Call:
tv_pagfl(formula = y ~ X + a, data = df, index = c("i_index",
"t_index"), lambda = 25, const_coef = "a")
S3 grouped_tv_plm const coef unbalanced summary
Call:
grouped_tv_plm(formula = y ~ X + a, data = df, groups = groups_0,
index = c("i_index", "t_index"), const_coef = "a")
Unbalanced panel: N = 10, T = 66-77, obs = 710
Information criterion: 0.28854
Residuals:
Min 1Q Median 3Q Max
-2.85704 -0.63292 0.01668 0.64120 2.77544
3 groups:
1 2 3 4 5 6 7 8 9 10
1 1 2 3 1 2 2 3 2 3
Constant coefficients:
a
Group 1 -0.02146
Group 2 -0.06506
Group 3 0.12088
Residual standard error: 1.01522 on 689 degrees of freedom
Mean squared error: 1.00019
Multiple R-squared: 0.81393, Adjusted R-squared: 0.80853
Code
estim
Output
Groups: 3
Call:
grouped_tv_plm(formula = y ~ X + a, data = df, groups = groups_0,
index = c("i_index", "t_index"), const_coef = "a")
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