graphics: Regression model plots

In ExpDes: Experimental Designs Package

Description

graphics Plots from regression models fitted in ANOVA.

Usage

graphics(
  a,
  degree = 1,
  mod = TRUE,
  main = " ",
  sub = " ",
  xlab = "Levels (X)",
  ylab = "Response var (Y)",
  pch = 19,
  xlim = NULL,
  ylim = NULL,
  bty = "o"
)

Arguments

a	Output from anova (performed in ExpDes).
degree	For polynomial models, 1 (linear model) is the default, 2 (quadratic model), 3 (cubic model), "pot" (Power model), "log" (Logistic model), "gom" (Gompertz model) and "exp" (Exponential model).
mod	Logic. Print the model expression and its R2 on the top of the graphic. The default is TRUE.
main	Title of the plot. Empty is the default.
sub	Subtitle of the plot. Empty is the default.
xlab	Name for axis X.
ylab	Name for axis Y.
pch	Caracter type to be used on the observed values.
xlim	Limits for axis X.
ylim	Limits for axis Y.
bty	Type of box the plot is fitted in.

Author(s)

Eric B Ferreira, [e-mail]

References

STEEL, R. G. D.; TORRIE, J. H. Principles and procedures in Statistics: a biometrical approach. McGraw-Hill, New York, NY. 1980.

See Also

reg.poly, plotres.

Examples

data(ex1)
attach(ex1)
a<-crd(trat, ig, quali=FALSE, nl=FALSE)
graphics(a, degree=1)
graphics(a, degree=2)
graphics(a, degree=3)

Example output

Attaching package: 'ExpDes'

The following object is masked from 'package:stats':

    ccf

------------------------------------------------------------------------
Analysis of Variance Table
------------------------------------------------------------------------
           DF     SS     MS     Fc     Pr>Fc
Treatament  3 214.88 71.626 6.5212 0.0029622
Residuals  20 219.67 10.984                 
Total      23 434.55                        
------------------------------------------------------------------------
CV = 3.41 %

------------------------------------------------------------------------
Shapiro-Wilk normality test
p-value:  0.91697 
According to Shapiro-Wilk normality test at 5% of significance, residuals can be considered normal.
------------------------------------------------------------------------

------------------------------------------------------------------------
Homogeneity of variances test
p-value:  0.1863216 
According to the test of bartlett at 5% of significance, residuals can be considered homocedastic.
------------------------------------------------------------------------

Adjustment of polynomial models of regression
------------------------------------------------------------------------

Linear Model
==========================================
   Estimate Standard.Error   tc    p.value
------------------------------------------
b0 100.2878     1.1320     88.5938    0   
b1 -0.4136      0.1210     -3.4177 0.0027 
------------------------------------------

R2 of linear model
--------
0.597077
--------

Analysis of Variance of linear model
================================================
              DF    SS       MS     Fc   p.value
------------------------------------------------
Linear Effect 1  128.2987 128.2987 11.68 0.00273
Lack of fit   2  86.5794  43.2897  3.94  0.03605
Residuals     20 219.6710 10.9835               
------------------------------------------------
------------------------------------------------------------------------

Quadratic Model
==========================================
   Estimate Standard.Error   tc    p.value
------------------------------------------
b0 101.5728     1.3187     77.0229    0   
b1 -1.1846      0.4236     -2.7968 0.0111 
b2  0.0514      0.0271     1.8995  0.0720 
------------------------------------------

R2 of quadratic model
--------
0.781504
--------

Analysis of Variance of quadratic model
===================================================
                 DF    SS       MS     Fc   p.value
---------------------------------------------------
Linear Effect    1  128.2987 128.2987 11.68 0.00273
Quadratic Effect 1  39.6294  39.6294  3.61  0.07202
Lack of fit      1  46.9500  46.9500  4.27  0.05187
Residuals        20 219.6710 10.9835               
---------------------------------------------------
------------------------------------------------------------------------

Cubic Model
==========================================
   Estimate Standard.Error   tc    p.value
------------------------------------------
b0 102.1983     1.3530     75.5350    0   
b1 -3.1445      1.0383     -3.0286 0.0066 
b2  0.4267      0.1835     2.3250  0.0307 
b3 -0.0167      0.0081     -2.0675 0.0519 
------------------------------------------

R2 of cubic model
-
1
-

Analysis of Variance of cubic model
===================================================
                 DF    SS       MS     Fc   p.value
---------------------------------------------------
Linear Effect    1  128.2987 128.2987 11.68 0.00273
Quadratic Effect 1  39.6294  39.6294  3.61  0.07202
Cubic Effect     1  46.9500  46.9500  4.27  0.05187
Lack of fit      0     0        0       0      1   
Residuals        20 219.6710 10.9835               
---------------------------------------------------
------------------------------------------------------------------------
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")

ExpDes documentation built on Oct. 5, 2021, 9:09 a.m.