regression {AgroReg}

Analysis: Regression linear or nonlinear

Description

This function is a simplification of all the analysis functions present in the package.

Usage

regression(
  trat,
  resp,
  model = "LM1",
  ylab = "Dependent",
  xlab = "Independent",
  theme = theme_classic(),
  legend.position = "top",
  point = "all",
  textsize = 12,
  pointsize = 4.5,
  linesize = 0.8,
  pointshape = 21,
  round = NA,
  fontfamily = "sans",
  error = "SE",
  width.bar = NA,
  xname.formula = "x",
  yname.formula = "y"
)

Arguments

trat

Numeric vector with dependent variable.

resp

Numeric vector with independent variable.

model

model regression (default is LM1)

ylab

Variable response name (Accepts the expression() function)

xlab

treatments name (Accepts the expression() function)

theme

ggplot2 theme (default is theme_classic())

legend.position

legend position (default is c(0.3,0.8))

point

defines whether you want to plot all points ("all") or only the mean ("mean")

textsize

Font size

pointsize

shape size

linesize

line size

pointshape

format point (default is 21)

round

round equation

fontfamily

Font family

error

Error bar (It can be SE - default, SD or FALSE)

width.bar

Bar width

xname.formula

Name of x in the equation

yname.formula

Name of y in the equation

Details

To change the regression model, change the "model" argument to:

1. N: Graph for not significant trend.

2. loess0: Loess non-parametric degree 0

3. loess1: Loess non-parametric degree 1

4. loess2: Loess non-parametric degree 2

5. LM0.5: Quadratic inverse

6. LM1: Linear regression.

7. LM2: Quadratic

8. LM3: Cubic

9. LM4: Quartic

10. LM0.5_i: Quadratic inverse without intercept.

11. LM1_i: Linear without intercept.

12. LM2_i: Quadratic regression without intercept.

13. LM3_i: Cubic without intercept.

14. LM4_i: Quartic without intercept.

15. LM13: Cubic without beta2

16. LM13i: Cubic inverse without beta2

17. LM23: Cubic without beta1

18. LM23i: Cubic inverse without beta2

19. LM2i3: Cubic without beta1, with inverse beta3

20. valcam: Valcam

21. L3: Three-parameter logistics.

22. L4: Four-parameter logistics.

23. L5: Five-parameter logistics.

24. LL3: Three-parameter log-logistics.

25. LL4: Four-parameter log-logistics.

26. LL5: Five-parameter log-logistics.

27. BC4: Brain-Cousens with four parameter.

28. BC5: Brain-Cousens with five parameter.

29. CD4: Cedergreen-Ritz-Streibig with four parameter.

30. CD5: Cedergreen-Ritz-Streibig with five parameter.

31. weibull3: Weibull with three parameter.

32. weibull4: Weibull with four parameter.

33. GP2: Gompertz with two parameter.

34. GP3: Gompertz with three parameter.

35. GP4: Gompertz with four parameter.

36. VB: Von Bertalanffy

37. lo3: Lorentz with three parameter

38. lo4: Lorentz with four parameter

39. beta: Beta

40. gaussian3: Analogous to the Gaussian model/Bragg with three parameters.

41. gaussian4: Analogous to the Gaussian model/Bragg with four parameters.

42. linear.linear: Linear-linear

43. linear.plateau: Linear-plateau

44. quadratic.plateau: Quadratic-plateau

45. plateau.linear: Plateau-linear

46. plateau.quadratic: Plateau-Quadratic

47. log: Logarithmic

48. log2: Logarithmic quadratic

49. thompson: Thompson

50. asymptotic: Exponential

51. asymptotic_neg: Exponential negative

52. asymptotic_i: Exponential without intercept.

53. asymptotic_ineg: Exponential negative without intercept.

54. biexponential: Biexponential

55. mitscherlich: Mitscherlich

56. yieldloss: Yield-loss

57. hill: Hill

58. MM2: Michaelis-Menten with two parameter.

59. MM3: Michaelis-Menten with three parameter.

60. SH: Steinhart-Hart

61. page: Page

62. newton: Newton

63. potential: Potential

64. midilli: Midilli

65. midillim: Modified Midilli

66. AM: Avhad and Marchetti

67. peleg: Peleg

68. VG: Vega-Galvez

Value

The function returns a list containing the coefficients and their respective values of p; statistical parameters such as AIC, BIC, pseudo-R2, RMSE (root mean square error); largest and smallest estimated value and the graph using ggplot2 with the equation automatically.

Examples

library(AgroReg)
data("aristolochia")
attach(aristolochia)
regression(trat, resp)