| MBriereE | R Documentation |
MBriereE is used to calculate y values at given x values using
the modified Brière equation or one of its simplified versions.
MBriereE(P, x, simpver = 1)
P |
the parameters of the modified Brière equation or one of its simplified versions. |
x |
the given |
simpver |
an optional argument to use the simplified version of the modified Brière equation. |
When simpver = NULL, the modified Brière equation is selected:
\mbox{if } x \in{\left(x_{\mathrm{min}}, \ x_{\mathrm{max}}\right)},
y = a\left|x(x-x_{\mathrm{min}})(x_{\mathrm{max}}-x)^{1/m}\right|^{\delta};
\mbox{if } x \notin{\left(x_{\mathrm{min}}, \ x_{\mathrm{max}}\right)},
y = 0.
Here, x and y represent the independent and dependent variables, respectively;
and a, m, x_{\mathrm{min}}, x_{\mathrm{max}}, and \delta are constants to be estimated,
where x_{\mathrm{min}} and x_{\mathrm{max}} represents the
lower and upper intersections between the curve and the x-axis. y is defined as 0
when x < x_{\mathrm{min}} or x > x_{\mathrm{max}}. There are five elements in P, representing
the values of a, m, x_{\mathrm{min}}, x_{\mathrm{max}}, and \delta, respectively.
\quad When simpver = 1, the simplified version 1 is selected:
\mbox{if } x \in{\left(0, \ x_{\mathrm{max}}\right)},
y = a\left|x^{2}(x_{\mathrm{max}}-x)^{1/m}\right|^{\delta};
\mbox{if } x \notin{\left(0, \ x_{\mathrm{max}}\right)},
y = 0.
There are four elements in P, representing
the values of a, m, x_{\mathrm{max}}, and \delta, respectively.
\quad When simpver = 2, the simplified version 2 is selected:
\mbox{if } x \in{\left(x_{\mathrm{min}}, \ x_{\mathrm{max}}\right)},
y = ax(x-x_{\mathrm{min}})(x_{\mathrm{max}}-x)^{1/m};
\mbox{if } x \notin{\left(x_{\mathrm{min}}, \ x_{\mathrm{max}}\right)},
y = 0.
There are four elements in P representing
the values of a, m, x_{\mathrm{min}}, and x_{\mathrm{max}}, respectively.
\quad When simpver = 3, the simplified version 3 is selected:
\mbox{if } x \in{\left(0, \ x_{\mathrm{max}}\right)},
y = ax^{2}(x_{\mathrm{max}}-x)^{1/m};
\mbox{if } x \notin{\left(0, \ x_{\mathrm{max}}\right)},
y = 0.
There are three elements in P representing
the values of a, m, and x_{\mathrm{max}}, respectively.
The y values predicted by the modified Brière equation or one of its simplified versions.
We have added a parameter \delta in the original Brière equation (i.e., simpver = 2) to increase the flexibility for data fitting.
Peijian Shi pjshi@njfu.edu.cn, Johan Gielis johan.gielis@uantwerpen.be, Brady K. Quinn Brady.Quinn@dfo-mpo.gc.ca.
Brière, J.-F., Pracros, P, Le Roux, A.-Y., Pierre, J.-S. (1999) A novel rate
model of temperature-dependent development for arthropods. Environmental
Entomology 28, 22-29. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/ee/28.1.22")}
Cao, L., Shi, P., Li, L., Chen, G. (2019) A new flexible sigmoidal growth model. Symmetry 11, 204. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3390/sym11020204")}
Jin, J., Quinn, B.K., Shi, P. (2022) The modified Brière equation and its applications. Plants 11, 1769. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3390/plants11131769")}
Shi, P., Gielis, J., Quinn, B.K., Niklas, K.J., Ratkowsky, D.A., Schrader, J., Ruan, H.,
Wang, L., Niinemets, Ü. (2022) 'biogeom': An R package for simulating and fitting natural
shapes. Annals of the New York Academy of Sciences 1516, 123-134. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/nyas.14862")}
areaovate, curveovate, fitovate, fitsigmoid,
MbetaE, MLRFE, MPerformanceE, sigmoid
x2 <- seq(-5, 15, len=2000)
Par2 <- c(0.01, 3, 0, 10, 1)
y2 <- MBriereE(P=Par2, x=x2, simpver=NULL)
dev.new()
plot( x2, y2, cex.lab=1.5, cex.axis=1.5, type="l",
xlab=expression(italic(x)), ylab=expression(italic(y)) )
graphics.off()
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