--- doc/homework/homework5.html 2001/06/01 14:17:04 1.4 +++ doc/homework/homework5.html 2001/06/12 21:05:31 1.5 @@ -4,7 +4,7 @@ LON-CAPA Homework System - +

LON-CAPA Homework System

Tags

@@ -300,10 +300,7 @@

<script> Functions

A list of functions that have been written that are available in - the Safe space scripting environment inside a problem. The eventual - goal is to provide all of the functions available in CAPA. Detailed - descriptions of each function and comparison with CAPA is given in - CAPA to LON-CAPA Functions. + the Safe space scripting environment inside a problem.

+ +

+ Detailed descriptions of each function and comparison with CAPA. +

@@ -485,7 +489,7 @@ y is real. $x can be a pure number. $m must be an integer and can be a pure integer number. $y can be a pure real number + jn(m,x) where m takes the value of 0, 1 or 2. jv(y,x) is new to LON-CAPA. @@ -496,7 +500,7 @@ yv(y,x), y is real. $x can be a pure number. $m must be an integer and can be a pure integer number. $y can be a pure real number + yn(m,x) where m takes the value of 0, 1 or 2. yv(y,x) is new to LON-CAPA. @@ -607,7 +611,8 @@ result in array B[i] where i = 0 to 4. The contents of B are as follows: B[0] = number of elements, B[1] = mean, B[2] = variance, B[3] = skewness and B[4] = kurtosis. - + @@ -626,16 +631,151 @@ - - - - - - + + + + + -
In CAPA, j0, j1 and jn are contained in one function, - jn(m,x) where m takes the value of 0, 1 or 2. jv(y,x) was not implemented
In CAPA, y0, y1 and yn are contained in one function, - yn(m,x) where m takes the value of 0, 1 or 2. yv(y,x) was not implemented
 In CAPA, the moments are passed as an array in the first argument whereas + in LON-CAPA, the array containing the moments are set equal to the function.
To destroy the contents of an array, use Use perl intrinsic undef function.
random_norma(...), random_beta(...), random_gamma(...), - random_exponential(...), random_poisson(...), random_chi(...), random_noncentral(...)Not yet implemented.  
random_normal (return_array,item_cnt,seed,av,std_dev)@return_array=&random_normal ($item_cnt,$seed,$av,$std_dev)Generate $item_cnt deviates of normal distribution of average $av and + standard deviation $std_dev. The distribution is generated from seed $seedIn CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function.
- + + random_beta (return_array,item_cnt,seed,aa,bb) + @return_array=&random_beta ($item_cnt,$seed,$aa,$bb)
+ NOTE: Both $aa and $bb MUST be greater than 1.0E-37. + Generate $item_cnt deviates of beta distribution. + The density of beta is: + X^($aa-1) *(1-X)^($bb-1) /B($aa,$bb) for 0<X<1. + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + random_gamma (return_array,item_cnt,seed,a,r) + @return_array=&random_gamma ($item_cnt,$seed,$a,$r)
+ NOTE: Both $a and $r MUST be positive. + Generate $item_cnt deviates of gamma distribution. + The density of gamma is: + ($a**$r)/gamma($r) * X**($r-1) * exp(-$a*X). + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + random_exponential (return_array,item_cnt,seed,av) + @return_array=&random_exponential ($item_cnt,$seed,$av)
+ NOTE: $av MUST be non-negative. + Generate $item_cnt deviates of exponential distribution. + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + random_poisson (return_array,item_cnt,seed,mu) + @return_array=&random_poisson ($item_cnt,$seed,$mu)
+ NOTE: $mu MUST be non-negative. + Generate $item_cnt deviates of poisson distribution. + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + random_chi (return_array,item_cnt,seed,df) + @return_array=&random_chi ($item_cnt,$seed,$df)
+ NOTE: $df MUST be positive. + Generate $item_cnt deviates of chi_square distribution with $df + degrees of freedom. + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + random_noncentral_chi (return_array,item_cnt,seed,df,nonc) + @return_array=&random_noncentral_chi ($item_cnt,$seed,$df,$nonc)
+ NOTE: $df MUST be at least 1 and $nonc MUST be non-negative. + Generate $item_cnt deviates of noncentral_chi_square + distribution with $df + degrees of freedom and noncentrality parameter $nonc. + In CAPA the results are passed as the first argument whereas in LON-CAPA + the results are set equal to the function. + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_f ($item_cnt,$seed,$dfn,$dfd)
+ NOTE: Both $dfn and $dfd MUST be positive. + Generate $item_cnt deviates of F (variance ratio) distribution with + degrees of freedom $dfn (numerator) and $dfd (denominator). + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_noncentral_f ($item_cnt,$seed,$dfn,$dfd,$nonc)
+ NOTE: $dfn must be at least 1, $dfd MUST be positive, and $nonc must + be non-negative. + Generate $item_cnt deviates of noncentral F (variance ratio) + distribution with degrees of freedom $dfn (numerator) and $dfd (denominator). + $nonc is the noncentrality parameter. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_multivariate_normal ($item_cnt,$seed,@mean,@covar)
+ NOTE: @mean should be a length p array of real numbers. @covar should be a length + p array of references to length p arrays or real numbers (i.e. a p by p matrix. + Generate $item_cnt deviates of multivariate_normal distribution with + mean vector @mean and variance-covariance matrix. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_multinomial ($item_cnt,$seed,@p)
+ NOTE: $item_cnt is rounded with int() and the result must be non-negative. + The number of elements in @p must be at least 2. + Returns single observation from multinomial distribution with + $item_cnt events classified into as many categories as the length of @p. + The probability of an event being classified into category i is given by + ith element of @p. The observation is an array with length equal to @p, so + when called in a scalar context it returns the length of @p. The sum of the + elements of the obervation is equal to $item_cnt. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_permutation ($item_cnt,@array) + Returns @array randomly permuted. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_uniform ($item_cnt,$seed,$low,$high)
+ NOTE: $low must be less than or equal to $high. + Generate $item_cnt deviates from a uniform distribution. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_uniform_integer ($item_cnt,$seed,$low,$high)
+ NOTE: $low and $high are both passed through int(). + $low must be less than or equal to $high. + Generate $item_cnt deviates from a uniform distribution in integers. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_binomial ($item_cnt,$seed,$nt,$p)
+ NOTE: $nt is rounded using int() and the result must be non-negative. + $p must be between 0 and 1 inclusive. + Generate $item_cnt deviates from the binomial distribution with + $nt trials and the probabilty of an event in each trial is $p. + New to LON-CAPA + + + NOT IMPLEMENTED IN CAPA + @return_array=&random_negative_binomial ($item_cnt,$seed,$ne,$p)
+ NOTE: $ne is rounded using int() and the result must be positive. + $p must be between 0 and 1 exclusive. + Generate an array of $item_cnt outcomes generated from + negative binomial distribution with + $ne events and the probabilty of an event in each trial is $p. + New to LON-CAPA + + +

<script> Variables