Find the derivatives with respect to x of the following:
\[ F(x|x \geq 0) = 1 - e^{\lambda*x} \]
library(Deriv)
# store function
f1=function(x)1-(exp(-lambda*x))
# derivative of function
ans=Deriv(f1)
ans
## function (x)
## lambda * exp(-(lambda * x))
\[ F(x|b>a) = \frac{x - a}{b-a} \]
# store function
f2=function(x)(x-a)/(b-a)
# derivative of function
ans=Deriv(f2)
ans
## function (x)
## 1/(b - a)
\[ F(x|a<x \leq c \leq b) = \frac{(x-a)^2}{(b-a)(c-a)} \]
# store function
f3=function(x)(x-a)^2/((b-a)(c-a))
# derivative of function
ans=Deriv(f3)
ans
## function (x)
## 2 * ((x - a)/(b - a)(c - a))
\[ F(x|a<x \leq c < x < b) = 1 - \frac{(b-x)^2}{(b-a)(c-a)} \]
# store function
f4=function(x)1-((b-x)^2/((b-a)(c-a)))
# derivative of function
ans=Deriv(f4)
ans
## function (x)
## 2 * ((b - x)/(b - a)(c - a))
Solve the following definite and indefinite integrals
\[ \int_{0}^{10}3x^{3}dx \]
# store function
f5=function(x)(3*(x^3))
# integrate definite integral
ans=integrate(Vectorize(f5),0,10)
ans
## 7500 with absolute error < 8.3e-11
\[ \int_{0}^{x}x\lambda e^{-\lambda*x} dx \]
library(mosaicCalc)
## Loading required package: mosaicCore
## Registered S3 method overwritten by 'mosaic':
## method from
## fortify.SpatialPolygonsDataFrame ggplot2
##
## Attaching package: 'mosaicCalc'
## The following object is masked from 'package:stats':
##
## D
# integrate indefinite integral
ans=antiD(x*lambda*exp(-lambda*x)~x)
ans
## function (x, lambda, C = 0)
## {
## numerical_integration(.newf, .wrt, as.list(match.call())[-1],
## formals(), from, ciName = intC, .tol)
## }
## <environment: 0x7ff9724b2620>
\[ \int_{0}^{.5}\frac{1}{b-a}dx \]
# assign values to variables a & b
a<-0
b<-1
# store function
f7=function(x)(1/(b-a))
# integrate definite integral
ans=integrate(Vectorize(f7),0,.5)
ans
## 0.5 with absolute error < 5.6e-15
\[ \int_{0}^{x}x\frac{1}{\Gamma(\alpha)\beta^\alpha}x^{\alpha-1}e^{-\beta x}dx \]
# integrate indefinite integral
ans=antiD(x^{alpha+1}/gamma*alpha*beta^{alpha}*e^{beta}~x)
## Warning in if (regexpr(rhsVar, deparse(lform[[2]], width.cutoff = 500))
## == : the condition has length > 1 and only the first element will be used
## Warning in if (regexpr(rhsVar, deparse(lform[[2]], width.cutoff = 500))
## == : the condition has length > 1 and only the first element will be used
## Warning in if (regexpr(rhsVar, deparse(lform[[2]], width.cutoff = 500))
## == : the condition has length > 1 and only the first element will be used
ans
## function (x, alpha, gamma, beta, e, C = 0)
## {
## numerical_integration(.newf, .wrt, as.list(match.call())[-1],
## formals(), from, ciName = intC, .tol)
## }
## <environment: 0x7ff9749ff1c0>
With the following matrix,
\[ \quad x=\begin{bmatrix} 1 & 2 & 3 \\ 3 & 3 & 1 \\ 4 & 6 & 8 \end{bmatrix} \]
Invert it using Gaussian row reduction.
library(matlib)
## Warning in rgl.init(initValue, onlyNULL): RGL: unable to open X11 display
## Warning: 'rgl_init' failed, running with rgl.useNULL = TRUE
# store matrix
A9<-rbind(c(1,2,3),c(3,3,1),c(4,6,8))
A9
## [,1] [,2] [,3]
## [1,] 1 2 3
## [2,] 3 3 1
## [3,] 4 6 8
# determine whether matrix is solvable
gaussianElimination(A9, numeric(3))
## [,1] [,2] [,3] [,4]
## [1,] 1 0 0 0
## [2,] 0 1 0 0
## [3,] 0 0 1 0
# find inverse matrix by elimination
gaussianElimination(A9, diag(3))
## [,1] [,2] [,3] [,4] [,5] [,6]
## [1,] 1 0 0 -4.5 -0.5 1.75
## [2,] 0 1 0 5.0 1.0 -2.00
## [3,] 0 0 1 -1.5 -0.5 0.75
ans = inv(A9)
ans
## [,1] [,2] [,3]
## [1,] -4.5 -0.5 1.75
## [2,] 5.0 1.0 -2.00
## [3,] -1.5 -0.5 0.75
# validate above solution by finding inverse using solve method
B9=solve(A9)
B9
## [,1] [,2] [,3]
## [1,] -4.5 -0.5 1.75
## [2,] 5.0 1.0 -2.00
## [3,] -1.5 -0.5 0.75
Find the determinant.
# find determinant of matrix
ans=det(A9)
ans
## [1] -4
Conduct LU decomposition.
library(pracma)
##
## Attaching package: 'pracma'
## The following objects are masked from 'package:matlib':
##
## angle, inv
## The following object is masked from 'package:mosaicCore':
##
## logit
# use lu() method for LU decomposition
ans=lu(A9)
ans
## $L
## [,1] [,2] [,3]
## [1,] 1 0.0000000 0
## [2,] 3 1.0000000 0
## [3,] 4 0.6666667 1
##
## $U
## [,1] [,2] [,3]
## [1,] 1 2 3.000000
## [2,] 0 -3 -8.000000
## [3,] 0 0 1.333333
Multiply the matrix by its inverse.
# multiply matrix A9 and its inverse B9
ans=A9%*%B9
ans
## [,1] [,2] [,3]
## [1,] 1.000000e+00 -2.220446e-16 4.440892e-16
## [2,] -4.440892e-16 1.000000e+00 2.220446e-16
## [3,] 0.000000e+00 0.000000e+00 1.000000e+00