[R] to findout maximized log likelihoods by using rlarg.fit (for several r order statistics)

From: rupos sujon <ruposh_at_yahoo.com>
Date: Wed 04 Apr 2007 - 12:00:35 GMT


Dear R helpers,

I need to find out maximized log likelihoods, parameters estimates and standard errors (in parentheses) of r largest-order statistics model, with different values of r by using the function rlarg.fit. I want to specify required number of order statistics to the model. I attached my data file with this mail.please help me.

Ruposh  

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>
> Message: 1
> Date: Tue, 3 Apr 2007 11:58:27 +0200
> From: Adelchi Azzalini <azzalini@stat.unipd.it>
> Subject: Re: [R] bivariate interpolation
> To: "eric lee" <ericlee100@gmail.com>
> Cc: r-help@stat.math.ethz.ch
> Message-ID:
> <20070403115827.99d67de3.azzalini@stat.unipd.it>
> Content-Type: text/plain; charset=ISO-8859-1
>
> On Tue, 3 Apr 2007 11:43:55 +0200, Adelchi Azzalini
> wrote:
>
> AA> On Mon, 2 Apr 2007 22:26:06 -0400, eric lee
> wrote:
> AA>
> AA> EL> Hi. I'm trying to take a data set with two
> independent and one
> AA> EL> dependent variable and enter a x,y value to
> predict the dependent
> AA> EL> with a nonparametric technique. I've been
> using interpp in the akima
> AA> EL> package, (windows xp, R 2.4.1), but get
> values that are orders of
> AA> EL> magnitude off when the predictors are
> slightly out of the range of
> AA> EL> the data set. Can you recommend a function
> for me? I've read that
> AA> EL> predict.loess has the same problem or just
> lists NA. Smooth.spline
> AA> EL> looks good, but can only do one predictor
> instead of bivariate. I've
> AA> EL> tried help.search("predict"), but couldn't
> find what I needed.
> AA> EL> Thanks.
> AA> EL>
> AA>
> AA> one option is to use sm.regression of package
> sm, along these lines
> AA>
> AA> x <- cbind(runif(100,-2, 2), runif(100,-2, 2))
> AA> y <- x[,1]^2 + x[,2]^2 + 0.7*x[,1]*x[,2] +
> rnorm(100)/3
> AA> sm.regression(x,y)
> AA> ev.pt <- rbind(c(-2,-2),c(2,2),
> c(2,-2),c(-2,2))
> AA> a <- sm.regression(x,y, eval.points=ev.pt,
> eval.grid=FALSE)
>
>
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year	month	rainfall
1910	7	153.5
1912	7	89.4
1912	7	165.5
1912	8	80.4
1915	7	122.1
1915	7	202
1915	8	94.1
1915	8	254.7
1916	6	121.8
1916	7	98.7
1916	9	175.3
1917	9	87.6
1918	8	88.2
1918	8	90.1
1918	8	150.6
1919	6	103.9
1919	7	89.1
1919	7	147.9
1919	8	104
1920	7	104
1920	7	110.4
1920	8	157.1
1920	8	354.7
1921	7	128.5
1922	7	96.4
1922	8	85.3
1922	8	127.3
1922	8	150.4
1923	6	101.1
1923	8	119.2
1925	7	85.6
1925	7	166.2
1925	7	183.3
1925	7	185.1
1925	8	89.2
1926	7	107.1
1926	7	150.8
1926	7	153.4
1926	8	93
1926	8	126.8
1927	7	121.7
1927	8	96.8
1928	8	99.3
1929	6	84.5
1929	7	126.9
1929	8	81.8
1930	7	100.2
1930	7	109.8
1930	7	133.9
1930	7	150.1
1931	7	122.3
1931	8	149.1
1932	8	143
1933	7	98.1
1933	7	125.2
1933	9	88.1
1934	9	97.2
1935	7	176.9
1935	7	179.3
1936	8	86.8
1936	8	87.4
1936	8	125.8
1937	9	89.1
1938	9	89.8
1940	7	88.7
1940	7	102.6
1940	7	106.7
1940	7	148.9
1940	7	180.8
1940	7	283.9
1940	9	221.1
1941	8	94.3
1942	8	106.2
1942	8	165.4
1945	6	105
1945	7	147.1
1945	8	88.6
1946	6	96.5
1946	6	106.8
1946	6	107.2
1946	6	117.2
1946	8	97.4
1947	7	159.4
1947	8	101.1
1948	6	106.5
1948	9	114.9
1954	7	126
1955	6	122.2
1956	6	219.9
1956	7	103
1956	7	115.4
1956	9	110.1
1956	9	176.4
1957	7	153.2
1958	7	145.3
1958	9	102.8
1959	7	101.9
1959	8	84.9
1959	8	100.7
1960	6	135.3
1960	7	88.9
1961	9	103.1
1963	6	91.9
1963	6	169.2
1963	7	174
1964	7	86.5
1964	7	89.4
1964	9	116.6
1964	9	126
1965	7	91.9
1965	7	108.8
1965	7	144.9
1965	8	90.8
1966	7	112.8
1966	7	113
1966	7	140
1966	7	226.3
1966	9	96.6
1967	7	96.2
1967	8	86.2
1968	7	91.9
1968	8	149.3
1968	9	100
1969	7	84.8
1969	8	89.4
1969	8	95.2
1969	9	119.8
1970	6	98.6
1970	7	82.3
1970	9	164.8
1971	7	188.6
1972	8	82.7
1972	8	84.7
1972	8	84.9
1972	8	179.2
1972	8	273.2
1974	8	84.3
1975	7	130.5
1976	8	96.2
1977	7	81.4
1977	7	155.8
1978	6	194.6
1979	8	92
1980	7	88.5
1980	8	105.9
1980	8	131
1981	7	82.5
1981	7	137
1982	7	106.8
1982	8	97.6
1983	9	131.6
1984	7	98.6
1984	8	97
1984	9	268.2
1985	7	84.3
1985	8	124.5
1986	7	147.8
1986	8	82.7
1986	8	84.4
1987	7	86.8
1987	7	294.6
1987	8	87.7
1988	7	101.6
1989	7	103.1
1990	6	81.7
1990	6	97.8
1990	6	100.7
1990	7	111
1990	8	88.5
1990	9	118.7
1990	9	120
1990	9	247.5
1991	7	140.2
1992	5	95.4
1992	8	130.3
1992	8	153.3
1992	9	87
1993	7	84.2
1993	7	91.8
1995	7	83.5
1995	7	88.2
1995	7	107.1
1995	8	82.3
1995	8	88.7
1995	8	110
1995	8	118.8
1995	8	126.1
1995	8	149.2
1996	6	83.2
1996	7	168.6
1997	5	90.4
1997	7	127.7
1998	6	85.7
1998	7	83
1998	8	108.9
1998	8	122.9
1998	8	211.4
1998	8	332.8
1999	8	163.5
1999	8	261.6
1999	9	101.4
1999	9	113.6
2000	8	82.3
2000	8	89.3
2000	8	122.9
2001	7	147.6
2001	7	273.4
2001	8	84.5
2002	8	120
2002	8	157.5
2002	8	178
2003	5	89.5
2003	7	173.5
2003	8	146.5
2003	8	177
2003	9	101
2004	6	84
2004	7	108.5
2005	6	95.5
2005	7	115
2005	9	90.5
2005	9	104.5
2006	5	93
2006	7	88
2006	7	195
2006	7	226.5
2006	7	241

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