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Interface to Popular R Functions for Data Science Pipelines

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sem: Interfaces for sem package for data science pipelines.

sem: Interfaces for sem package for data science pipelines.
In intubate: Interface to Popular R Functions for Data Science Pipelines

Description Usage Arguments Details Value Author(s) Examples

Description

Interfaces to sem functions that can be used in a pipeline implemented by magrittr.

Usage

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ntbt_rawMoments(data, ...)
ntbt_sem(data, ...)
ntbt_tsls(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

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## Not run: 
library(intubate)
library(magrittr)
library(sem)


## ntbt_rawMoments: Compute Raw Moments Matrix
## Original function to interface
rawMoments(~ Q + P + D + F + A, data = Kmenta)

## The interface puts data as first parameter
ntbt_rawMoments(Kmenta, ~ Q + P + D + F + A)

## so it can be used easily in a pipeline.
Kmenta %>%
  ntbt_rawMoments(~ Q + P + D + F + A)


## ntbt_sem: General Structural Equation Models
## NOTE: this example is NOT using the formula interface.
##       It is creating a list with the variables.
R.DHP <- readMoments(diag=FALSE, names=c("ROccAsp", "REdAsp", "FOccAsp", 
                "FEdAsp", "RParAsp", "RIQ", "RSES", "FSES", "FIQ", "FParAsp"),
                text="
    .6247     
    .3269  .3669       
    .4216  .3275  .6404
    .2137  .2742  .1124  .0839
    .4105  .4043  .2903  .2598  .1839
    .3240  .4047  .3054  .2786  .0489  .2220
    .2930  .2407  .4105  .3607  .0186  .1861  .2707
    .2995  .2863  .5191  .5007  .0782  .3355  .2302  .2950
    .0760  .0702  .2784  .1988  .1147  .1021  .0931 -.0438  .2087
")

model.dhp.1 <- specifyEquations(covs="RGenAsp, FGenAsp", text="
RGenAsp = gam11*RParAsp + gam12*RIQ + gam13*RSES + gam14*FSES + beta12*FGenAsp
FGenAsp = gam23*RSES + gam24*FSES + gam25*FIQ + gam26*FParAsp + beta21*RGenAsp
ROccAsp = 1*RGenAsp
REdAsp = lam21(1)*RGenAsp  # to illustrate setting start values
FOccAsp = 1*FGenAsp
FEdAsp = lam42(1)*FGenAsp
")

dta <- list(R.DHP = R.DHP, model.dhp.1 = model.dhp.1)
rm(R.DHP, model.dhp.1)

## Original function to interface
attach(dta)
sem.dhp.1 <- ntbt_sem(model.dhp.1, R.DHP, 329,
                      fixed.x=c('RParAsp', 'RIQ', 'RSES', 'FSES', 'FIQ', 'FParAsp'))
summary(sem.dhp.1)
detach()

## The interface puts data as first parameter
sem.dhp.1 <- ntbt_sem(dta, model.dhp.1, R.DHP, 329,
                      fixed.x=c('RParAsp', 'RIQ', 'RSES', 'FSES', 'FIQ', 'FParAsp'))
summary(sem.dhp.1)

## so it can be used easily in a pipeline.
dta %>%
  ntbt_sem(model.dhp.1, R.DHP, 329,
           fixed.x=c('RParAsp', 'RIQ', 'RSES', 'FSES', 'FIQ', 'FParAsp')) %>%
  summary()


## ntbt_tsls: Two-Stage Least Squares
## Original function to interface
tsls(Q ~ P + D, ~ D + F + A, data = Kmenta)

## The interface puts data as first parameter
ntbt_tsls(Kmenta, Q ~ P + D, ~ D + F + A)

## so it can be used easily in a pipeline.
Kmenta %>%
  ntbt_tsls(Q ~ P + D, ~ D + F + A)

## End(Not run)

Example output

sh: 1: cannot create /dev/null: Permission denied
sh: 1: cannot create /dev/null: Permission denied

Raw Moments
          Intercept          Q          P        D        F        A
Intercept    1.0000   100.8982   100.0191   97.535   96.625   10.500
Q          100.8982 10193.8525 10093.8167 9873.665 9780.155 1062.599
P          100.0191 10093.8167 10037.1729 9793.092 9651.145 1050.194
D           97.5350  9873.6647  9793.0919 9646.038 9494.644 1045.960
F           96.6250  9780.1547  9651.1453 9494.644 9489.828  994.060
A           10.5000  1062.5988  1050.1941 1045.960  994.060  143.500

N =  20 

Raw Moments
          Intercept          Q          P        D        F        A
Intercept    1.0000   100.8982   100.0191   97.535   96.625   10.500
Q          100.8982 10193.8525 10093.8167 9873.665 9780.155 1062.599
P          100.0191 10093.8167 10037.1729 9793.092 9651.145 1050.194
D           97.5350  9873.6647  9793.0919 9646.038 9494.644 1045.960
F           96.6250  9780.1547  9651.1453 9494.644 9489.828  994.060
A           10.5000  1062.5988  1050.1941 1045.960  994.060  143.500

N =  20 

Raw Moments
          Intercept          Q          P        D        F        A
Intercept    1.0000   100.8982   100.0191   97.535   96.625   10.500
Q          100.8982 10193.8525 10093.8167 9873.665 9780.155 1062.599
P          100.0191 10093.8167 10037.1729 9793.092 9651.145 1050.194
D           97.5350  9873.6647  9793.0919 9646.038 9494.644 1045.960
F           96.6250  9780.1547  9651.1453 9494.644 9489.828  994.060
A           10.5000  1062.5988  1050.1941 1045.960  994.060  143.500

N =  20 
Read 45 items
Read 6 items
NOTE: adding 4 variances to the model

 Model Chisquare =  26.69722   Df =  15 Pr(>Chisq) = 0.03130238
 AIC =  64.69722
 BIC =  -60.24365

 Normalized Residuals
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
-0.79953 -0.11783  0.00000 -0.01201  0.03974  1.56525 

 R-square for Endogenous Variables
RGenAsp FGenAsp ROccAsp  REdAsp FOccAsp  FEdAsp 
 0.5220  0.6170  0.5879  0.6639  0.6888  0.5954 

 Parameter Estimates
                   Estimate    Std Error  z value    Pr(>|z|)    
gam11               0.16122238 0.03879229  4.1560415 3.238091e-05
gam12               0.24964951 0.04398093  5.6763131 1.376288e-08
gam13               0.21840339 0.04419737  4.9415476 7.750487e-07
gam14               0.07183929 0.04970696  1.4452563 1.483859e-01
beta12              0.18423232 0.09488787  1.9415793 5.218805e-02
gam23               0.06188691 0.05171968  1.1965835 2.314690e-01
gam24               0.22886711 0.04416218  5.1824232 2.190216e-07
gam25               0.34903540 0.04528979  7.7067130 1.290997e-14
gam26               0.15953413 0.03882593  4.1089578 3.974486e-05
beta21              0.23547779 0.11938929  1.9723527 4.856936e-02
lam21               1.06267767 0.09013865 11.7893677 4.428532e-32
lam42               0.92972555 0.07028108 13.2286752 5.993451e-40
V[RGenAsp]          0.28098694 0.04623153  6.0778199 1.218274e-09
C[RGenAsp,FGenAsp] -0.02260935 0.05119391 -0.4416413 6.587488e-01
V[FGenAsp]          0.26383537 0.04466688  5.9067334 3.489577e-09
V[ROccAsp]          0.41214523 0.05122464  8.0458399 8.565593e-16
V[REdAsp]           0.33614544 0.05209991  6.4519386 1.104283e-10
V[FOccAsp]          0.31119476 0.04592712  6.7758385 1.236868e-11
V[FEdAsp]           0.40460387 0.04618438  8.7606206 1.941783e-18
                                       
gam11              RGenAsp <--- RParAsp
gam12              RGenAsp <--- RIQ    
gam13              RGenAsp <--- RSES   
gam14              RGenAsp <--- FSES   
beta12             RGenAsp <--- FGenAsp
gam23              FGenAsp <--- RSES   
gam24              FGenAsp <--- FSES   
gam25              FGenAsp <--- FIQ    
gam26              FGenAsp <--- FParAsp
beta21             FGenAsp <--- RGenAsp
lam21              REdAsp <--- RGenAsp 
lam42              FEdAsp <--- FGenAsp 
V[RGenAsp]         RGenAsp <--> RGenAsp
C[RGenAsp,FGenAsp] FGenAsp <--> RGenAsp
V[FGenAsp]         FGenAsp <--> FGenAsp
V[ROccAsp]         ROccAsp <--> ROccAsp
V[REdAsp]          REdAsp <--> REdAsp  
V[FOccAsp]         FOccAsp <--> FOccAsp
V[FEdAsp]          FEdAsp <--> FEdAsp  

 Iterations =  32 

 Model Chisquare =  26.69722   Df =  15 Pr(>Chisq) = 0.03130238
 AIC =  64.69722
 BIC =  -60.24365

 Normalized Residuals
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
-0.79953 -0.11783  0.00000 -0.01201  0.03974  1.56525 

 R-square for Endogenous Variables
RGenAsp FGenAsp ROccAsp  REdAsp FOccAsp  FEdAsp 
 0.5220  0.6170  0.5879  0.6639  0.6888  0.5954 

 Parameter Estimates
                   Estimate    Std Error  z value    Pr(>|z|)    
gam11               0.16122238 0.03879229  4.1560415 3.238091e-05
gam12               0.24964951 0.04398093  5.6763131 1.376288e-08
gam13               0.21840339 0.04419737  4.9415476 7.750487e-07
gam14               0.07183929 0.04970696  1.4452563 1.483859e-01
beta12              0.18423232 0.09488787  1.9415793 5.218805e-02
gam23               0.06188691 0.05171968  1.1965835 2.314690e-01
gam24               0.22886711 0.04416218  5.1824232 2.190216e-07
gam25               0.34903540 0.04528979  7.7067130 1.290997e-14
gam26               0.15953413 0.03882593  4.1089578 3.974486e-05
beta21              0.23547779 0.11938929  1.9723527 4.856936e-02
lam21               1.06267767 0.09013865 11.7893677 4.428532e-32
lam42               0.92972555 0.07028108 13.2286752 5.993451e-40
V[RGenAsp]          0.28098694 0.04623153  6.0778199 1.218274e-09
C[RGenAsp,FGenAsp] -0.02260935 0.05119391 -0.4416413 6.587488e-01
V[FGenAsp]          0.26383537 0.04466688  5.9067334 3.489577e-09
V[ROccAsp]          0.41214523 0.05122464  8.0458399 8.565593e-16
V[REdAsp]           0.33614544 0.05209991  6.4519386 1.104283e-10
V[FOccAsp]          0.31119476 0.04592712  6.7758385 1.236868e-11
V[FEdAsp]           0.40460387 0.04618438  8.7606206 1.941783e-18
                                       
gam11              RGenAsp <--- RParAsp
gam12              RGenAsp <--- RIQ    
gam13              RGenAsp <--- RSES   
gam14              RGenAsp <--- FSES   
beta12             RGenAsp <--- FGenAsp
gam23              FGenAsp <--- RSES   
gam24              FGenAsp <--- FSES   
gam25              FGenAsp <--- FIQ    
gam26              FGenAsp <--- FParAsp
beta21             FGenAsp <--- RGenAsp
lam21              REdAsp <--- RGenAsp 
lam42              FEdAsp <--- FGenAsp 
V[RGenAsp]         RGenAsp <--> RGenAsp
C[RGenAsp,FGenAsp] FGenAsp <--> RGenAsp
V[FGenAsp]         FGenAsp <--> FGenAsp
V[ROccAsp]         ROccAsp <--> ROccAsp
V[REdAsp]          REdAsp <--> REdAsp  
V[FOccAsp]         FOccAsp <--> FOccAsp
V[FEdAsp]          FEdAsp <--> FEdAsp  

 Iterations =  32 

 Model Chisquare =  26.69722   Df =  15 Pr(>Chisq) = 0.03130238
 AIC =  64.69722
 BIC =  -60.24365

 Normalized Residuals
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
-0.79953 -0.11783  0.00000 -0.01201  0.03974  1.56525 

 R-square for Endogenous Variables
RGenAsp FGenAsp ROccAsp  REdAsp FOccAsp  FEdAsp 
 0.5220  0.6170  0.5879  0.6639  0.6888  0.5954 

 Parameter Estimates
                   Estimate    Std Error  z value    Pr(>|z|)    
gam11               0.16122238 0.03879229  4.1560415 3.238091e-05
gam12               0.24964951 0.04398093  5.6763131 1.376288e-08
gam13               0.21840339 0.04419737  4.9415476 7.750487e-07
gam14               0.07183929 0.04970696  1.4452563 1.483859e-01
beta12              0.18423232 0.09488787  1.9415793 5.218805e-02
gam23               0.06188691 0.05171968  1.1965835 2.314690e-01
gam24               0.22886711 0.04416218  5.1824232 2.190216e-07
gam25               0.34903540 0.04528979  7.7067130 1.290997e-14
gam26               0.15953413 0.03882593  4.1089578 3.974486e-05
beta21              0.23547779 0.11938929  1.9723527 4.856936e-02
lam21               1.06267767 0.09013865 11.7893677 4.428532e-32
lam42               0.92972555 0.07028108 13.2286752 5.993451e-40
V[RGenAsp]          0.28098694 0.04623153  6.0778199 1.218274e-09
C[RGenAsp,FGenAsp] -0.02260935 0.05119391 -0.4416413 6.587488e-01
V[FGenAsp]          0.26383537 0.04466688  5.9067334 3.489577e-09
V[ROccAsp]          0.41214523 0.05122464  8.0458399 8.565593e-16
V[REdAsp]           0.33614544 0.05209991  6.4519386 1.104283e-10
V[FOccAsp]          0.31119476 0.04592712  6.7758385 1.236868e-11
V[FEdAsp]           0.40460387 0.04618438  8.7606206 1.941783e-18
                                       
gam11              RGenAsp <--- RParAsp
gam12              RGenAsp <--- RIQ    
gam13              RGenAsp <--- RSES   
gam14              RGenAsp <--- FSES   
beta12             RGenAsp <--- FGenAsp
gam23              FGenAsp <--- RSES   
gam24              FGenAsp <--- FSES   
gam25              FGenAsp <--- FIQ    
gam26              FGenAsp <--- FParAsp
beta21             FGenAsp <--- RGenAsp
lam21              REdAsp <--- RGenAsp 
lam42              FEdAsp <--- FGenAsp 
V[RGenAsp]         RGenAsp <--> RGenAsp
C[RGenAsp,FGenAsp] FGenAsp <--> RGenAsp
V[FGenAsp]         FGenAsp <--> FGenAsp
V[ROccAsp]         ROccAsp <--> ROccAsp
V[REdAsp]          REdAsp <--> REdAsp  
V[FOccAsp]         FOccAsp <--> FOccAsp
V[FEdAsp]          FEdAsp <--> FEdAsp  

 Iterations =  32 

Model Formula: Q ~ P + D

Instruments: ~D + F + A

Coefficients:
(Intercept)           P           D 
 94.6333039  -0.2435565   0.3139918 


Model Formula: Q ~ P + D

Instruments: ~D + F + A

Coefficients:
(Intercept)           P           D 
 94.6333039  -0.2435565   0.3139918 


Model Formula: Q ~ P + D
<environment: 0x5628a150fbe8>

Instruments: ~D + F + A
<environment: 0x5628a150fbe8>

Coefficients:
(Intercept)           P           D 
 94.6333039  -0.2435565   0.3139918

intubate documentation built on May 2, 2019, 2:46 p.m.

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