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  • Regress

    2020-12-07 11:23:37
    <p>This Pull Request fixes/closes #478. ... - Uses regress instead of regex Current issues: -Refactoring regexp/mod.rs with regress.</p><p>该提问来源于开源项目:boa-dev/boa</p></div>
  • REGRESS

    2016-01-27 15:20:23
    REGRESS Multiple linear regression using least squares.​ 使用最小二乘法多元线性回归。 1. B = REGRESS(Y,X)  returns the vector B of regression coefficients in the linear model Y = X*B. X is an n...

     REGRESS Multiple linear regression using least squares.​

    使用最小二乘法多元线性回归。

    1.  B = REGRESS(Y,X)

     returns the vector B of regression coefficients in the    linear model Y = X*B.  X is an n-by-p design matrix, with rows corresponding to observations and columns to predictor variables.  Y is an n-by-1 vector of response observations.     ​

    返回返回线性模型Y=X*B的拟合系数矢量B。X是一个设计的 n x p 的矩阵,它的行对应观测值,列对应预测值。Y是一个n x 1的观测的响应向量。

    2. [B,BINT] = REGRESS(Y,X)

    returns a matrix BINT of 95% confidence    intervals for B.    

    返回一个矩阵BINT,代表着矩阵B 95%的置信区间。 

    3. [B,BINT,R] = REGRESS(Y,X)

    returns a vector R of residuals.   ​

    返回残差矢量R

    4. [B,BINT,R,RINT] = REGRESS(Y,X)

    returns a matrix RINT of intervals that can be used to diagnose outliers.  If RINT(i,:) does not contain zero,    then the i-th residual is larger than would be expected, at the 5%    significance level.  This is evidence that the I-th observation is an    outlier.    ​

    返回一个可以诊断异常值的区间--矩阵RINT,如果RINT的第 i 行没有0,那么第 i 行的残差比预期的5%的显著水品大。这证明 I 行观测值是离群的。

     5. [B,BINT,R,RINT,STATS] = REGRESS(Y,X)

    returns a vector STATS containing, in the following order, the R-square statistic, the F statistic and p value    for the full model, and an estimate of the error variance.     ​

    返回一个矢量STATS依次包含:​

    6. [...] = REGRESS(Y,X,ALPHA)

    uses a 100*(1-ALPHA)% confidence level to    compute BINT, and a (100*ALPHA)% significance level to compute RINT.    

     使用100*(1-α)%的置信水平来计算BINT,使用100α%的

    X should include a column of ones so that the model contains a constant    term.  The F statistic and p value are computed under the assumption    that the model contains a constant term, and they are not correct for    models without a constant.  The R-square value is one minus the ratio of    the error sum of squares to the total sum of squares.  This value can    be negative for models without a constant, which indicates that the    model is not appropriate for the data.    

    If columns of X are linearly dependent, REGRESS sets the maximum    possible number of elements of B to zero to obtain a "basic solution",    and returns zeros in elements of BINT corresponding to the zero    elements of B.​​

    如果X的列都线性相关,REGRESS 将

    REGRESS treats NaNs(Not a Number) in X or Y as missing values, and removes them.​

    拟合函数对于X或者Y里面的非数值的元素,认为他们是缺失的,并删除他们。

     

    展开全文
  • regress

    2016-09-13 09:57:00
    spool invalid_obj_before_regress.lst select owner,object_name,object_type,last_ddl_time from dba_objects where status='INVALID'; spool off EOF   ############################################ ...

    #! /bin/ksh

    ############### ###   UAT   ### ###############

    export ENVS=/test/change/env/env_test.sql

    export SCHEMA_HOME=/test/change/schema/test/2015_11_20_test_1.1

    export SCHEMA_HOME_test=${SCHEMA_HOME}/2015_11_20_test

    ################ ###   PROD   ### ################

    #export ENVS=

    #export SCHEMA_HOME=

    #export SCHEMA_HOME_test=

    ##################################### # Check DB connection is correct #####################################

    sqlplus /nolog <<EOF

    set pagesize 500

    set linesize 200

    @${ENVS}

    connect &v_system_un/&v_system_pw@&v_conn_str

    show user prompt &v_conn_str

    select * from v\$instance;

    EOF

     

    echo Press any key to continue

    read ANS

     

    ############################################ # Check invalid objects (before)

    ############################################
    cd $SCHEMA_HOME
    sqlplus /nolog << EOF
    @${ENVS}
    connect &v_system_un/&v_system_pw@&v_conn_str
    set pages 1000
    set lines 150
    col owner for a15
    col object_name for a35
    col object_type for a20
    col last_ddl_time for a20
    alter session set nls_date_format = 'YYYY-MON-DD HH24:MI:SS';
    spool invalid_obj_before_regress.lst
    select owner,object_name,object_type,last_ddl_time from dba_objects where status='INVALID';
    spool off
    EOF

     

    ############################################ banner 'SMAS' ############################################

    date

    echo Press any key to continue

    read ANS

    cd $SCHEMA_HOME_SMAS/

    sqlplus /nolog << EOF

    set pagesize 500

    set linesize 200

    @${ENVS}

    connect &v_system_un/&v_system_pw@&v_conn_str

    show user

    select * from v\$instance;

    select to_char(sysdate,'YYYY-MON-DD HH24:MI:SS')  from dual;

    @01_change_regress.sql

    EOF

    date

    echo Press any key to continue

    read ANS

    ############################################ # Check invalid objects (after) ############################################

    cd $SCHEMA_HOME

    sqlplus /nolog << EOF

    @${ENVS}

    connect &v_system_un/&v_system_pw@&v_conn_str

    set pages 1000

    set lines 150

    col owner for a15

    col object_name for a35

    col last_ddl_time for a20
    alter session set nls_date_format = 'YYYY-MON-DD HH24:MI:SS';
    spool invalid_obj_after_regress.lst
    select owner,object_name,object_type,last_ddl_time from dba_objects where status='INVALID';
    spool off
    EOF

     

    转载于:https://www.cnblogs.com/feiyun8616/p/5867382.html

    展开全文
  • MATLAB regress命令

    万次阅读 多人点赞 2018-04-03 16:46:24
    1 regress命令 用于一元及多元线性回归,本质上是最小二乘法。在Matlab 2014a中,输入help ... 调用格式:B = regress(Y,X)[B,BINT] = regress(Y,X)[B,BINT,R] = regress(Y,X)[B,BINT,R,RINT] = regress(Y,X)B,BINT,...

    1 regress命令

     

        用于一元及多元线性回归,本质上是最小二乘法。在Matlab 命令行窗口输入help regress ,会弹出和regress的相关信息,一一整理。

        调用格式:

    • B = regress(Y,X)
    • [B,BINT] = regress(Y,X)
    • [B,BINT,R] = regress(Y,X)
    • [B,BINT,R,RINT] = regress(Y,X)
    • B,BINT,R,RINT,STATS] = regress(Y,X)
    • [...] = regress(Y,X,ALPHA)

     

        参数解释:

    • B:回归系数,是个向量(“the vector B of regression coefficients in the  linear model Y = X*B”)。
    • BINT:回归系数的区间估计(“a matrix BINT of 95% confidence intervals for B”)。
    • R:残差( “a vector R of residuals”)。
    • RINT:置信区间(“a matrix RINT of intervals that can be used to diagnose outliers”)。
    • STATS:用于检验回归模型的统计量。有4个数值:判定系数R^2,F统计量观测值,检验的p的值,误差方差的估计。
    • ALPHA:显著性水平(缺少时为默认值0.05)。

     

    2 regress函数例程

    目标函数:y=Ax1^2+Bx2^2+Cx1+Dx2+Ex1*x2+F  (这是一个二次函数,两个变量,大写的字母是常数)

    应用实例:

    %导入数据   
    x1=[7666 7704 8148 8571 8679 7704 6471 5870 5289 3815 3335 2927 2758 2591]';  
    x2=[16.22 16.85 17.93 17.28 17.23 17 19 18.22 16.3 13.37 11.62 10.36 9.83 9.25]'; 
    y=[7613.51  7850.91  8381.86  9142.81 10813.6 8631.43 8124.94 9429.79 10230.81 10163.61 9737.56 8561.06 7781.82 7110.97]'; 
    X=[ones(size(y)) x1.^2 x2.^2 x1 x2 x1.*x2];  
      
    %开始分析  
    [b,bint,r,rint,stats] = regress(y,X);
     
    其中, b(1)=F(最后那个常数项)
               b(2)=A,b(3)=B,b(4)=C,b(5)=D,b(6)=E。bint为b的95%置信区间。

    比较重要的stats分析stats的第三个参数为F检测的P值,p值很小(P<0.001),说明拟合模型有效。

     

    可视化操作:

    figure,scatter3(x1,x2,y,'filled') %scatter可用于画散点图
    %拟合,三维视图显示  
    hold on  %在刚刚那副散点图上接着画  
    x1fit = min(x1):100:max(x1);   %设置x1的数据间隔  
    x2fit = min(x2):1:max(x2);     %设置x2的数据间隔  
    [X1FIT,X2FIT] = meshgrid(x1fit,x2fit);    %生成一个二维网格平面,也可以说生成X1FIT,X2FIT的坐标  
    YFIT=b(1)+b(2)*X1FIT.^2+b(3)*X2FIT.^2+b(4)*X1FIT +b(5)*X2FIT+b(6)*X1FIT.*X2FIT;    %代入已经求得的参数,拟合函数式  
    mesh(X1FIT,X2FIT,YFIT)    %X1FIT,X2FIT是网格坐标矩阵,YFIT是网格点上的高度矩阵  
    view(10,10)  %改变角度观看已存在的三维图,第一个10表示方位角,第二个表示俯视角。  
                 %方位角相当于球坐标中的经度,俯视角相当于球坐标中的纬度  
    xlabel('x1') %设置x轴的名称  
    ylabel('x2') %设置y轴的名称  
    zlabel('y')  %设置z轴的名称

     

    下面来用一组数据对上面的效果进行检测,自己建立一个方程:

    目标函数:y=5x1^2+7x2^2+2x1+3x2+8x1*x2+10

    %测试数据
    x1_test = [-1, 0, 1, -1, 0, 1]';  %
    x2_test = [-1, -1, 0, 1, 0, 1]'; %
    y_test = [25, 14, 17, 15, 10, 35]'; %
    
    X_test=[ones(size(y_test)) x1_test.^2 x2_test.^2 x1_test x2_test x1_test.*x2_test];  
    
    %开始分析  
    [b_test,bint_test,r,rint_test,stats_test] = regress(y_test,X_test); 
    
    figure,
    scatter3(x1_test,x2_test,y_test,'filled') %scatter可用于画散点图
    %拟合,三维视图显示  
    hold on  %在刚刚那副散点图上接着画  
    x1fit = min(x1_test):0.1:max(x1_test);   %设置x1的数据间隔  
    x2fit = min(x2_test):0.1:max(x2_test);     %设置x2的数据间隔  
    [X1FIT,X2FIT] = meshgrid(x1fit,x2fit);    %生成一个二维网格平面,也可以说生成X1FIT,X2FIT的坐标  
    YFIT=b_test(1)+b_test(2)*X1FIT.^2+b_test(3)*X2FIT.^2+b_test(4)*X1FIT +b_test(5)*X2FIT+b_test(6)*X1FIT.*X2FIT;    %代入已经求得的参数,拟合函数式  
    mesh(X1FIT,X2FIT,YFIT)    %X1FIT,X2FIT是网格坐标矩阵,YFIT是网格点上的高度矩阵  
    view(10,10)  %改变角度观看已存在的三维图,第一个10表示方位角,第二个表示俯视角。  
                 %方位角相当于球坐标中的经度,俯视角相当于球坐标中的纬度  
    xlabel('x1') %设置x轴的名称  
    ylabel('x2') %设置y轴的名称  
    zlabel('y')  %设置z轴的名称

     拟合效果如下:


     

    参考文献:

    https://wenku.baidu.com/view/5b7cd4307cd184254b3535ac.html

    展开全文
  • python_regress-源码

    2021-03-31 20:34:34
    python_regress
  • GDT regress test

    2021-01-10 07:53:13
    <div><p>GDT regress test based on my GDT setting sample</p><p>该提问来源于开源项目:unicorn-engine/unicorn</p></div>
  • Regress out covariates

    2020-12-09 04:46:18
    Was wondering how to regress out covariates other than nUMI. My code is as below. When I try to regress out orig.ident, there is an error. <p>A = sample(1:ncol(combined$sc.data), 2000) annot=...
  • <div><p>https://v8.imgtec.com/bbv8/builders/Target%20-%20edge/builds/10305/steps/Check/logs/regress-336820 The test finishes with error messages - "allocation failure GC in old space requested&#...
  • 多元线性回归在Matlab统计工具箱中使用命令regress()实现多元线性回归,调用格式为b=regress(y,x)或[b,bint,r,rint,statsl = regess(y,x,alpha)其中因变量数据向量y和自变量数据矩阵x按以下排列方式输入对...

    一、回归分析

    1.多元线性回归

    在Matlab统计工具箱中使用命令regress()实现多元线性回归,调用格式为

    b=regress(y,x)

    [b,bint,r,rint,statsl = regess(y,x,alpha)

    其中因变量数据向量y和自变量数据矩阵x按以下排列方式输入对一元线性回归,取k=1即可。alpha为显著性水平(缺省时设定为0.05),输出向量b,bint为回归系数估计值和它们的置信区间,r,rint为残差及其置信区间,stats是用于检验回归模型的统计量,有三个数值,第一个是R2,其中R 是相关系数,第二个是F统计量值,第三个是与统计量F对应的概率P,当P

    时拒绝H0,回归模型成立。

    画出残差及其置信区间,用命令rcoplot(r,rint)实例1:已知某湖八年来湖水中COD浓度实测值(y)与影响因素湖区工业产值(x1)、总人口数(x2)、捕鱼量(x3)、降水量(x4)资料,建立污染物y的水质分析模

    型。

    (1)输入数据

    x1=[1.376, 1.375, 1.387, 1.401, 1.412, 1.428, 1.445, 1.477]

    x2=[0.450, 0.475, 0.485, 0.500, 0.535, 0.545, 0.550, 0.575]

    x3=[2.170 ,2.554, 2.676, 2.713, 2.823, 3.088, 3.122, 3.262] x4=[0.8922, 1.1610 ,0.5346, 0.9589, 1.0239, 1.0499, 1.1065, 1.1387] y=[5.19, 5.30, 5.60,5.82,6.00, 6.06,6.45,6.95]

    (2)保存数据(以数据文件.mat形式保存,便于以后调用)

    save data x1 x2 x3 x4 y

    load data (取出数据)

    (3)执行回归命令

    x =[ones(8,1),];

    [b,bint,r,rint,stats] = regress

    得结果:

    b = (-16.5283,15.7206,2.0327,-0.2106,-0.1991)’

    stats = (0.9908,80.9530,0.0022)

    = -16.5283 + 15.7206xl + 2.0327x2 - 0.2106x3 + 0.1991x4

    R2 = 0.9908,F = 80.9530,P = 0.0022

    展开全文
  • <div><p>https://v8.mips.com/bbv8/builders/Target%20-%20MIPS64%20-%20edge%20-%20clang/builds/1672/steps/Check%20%28flakes%29/logs/regress-crbug-514081 ...
  • https://v8.mips.com/bbv8/builders/Target%20-%20big%20-%20edge%20-%20no%20i18n/builds/8282/steps/Check/logs/regress-353004 Fails on mips and mips64 big endian build bots.</p><p>该提问来源于开源项目&#...
  • Upgraded regress to 0.2.0

    2020-11-29 21:08:50
    It bumps <code>regress</code> to 0.2, which brings many nice and new features and fixes. I also took the opportunity to reduce a bit the size of the <code>RegExp</code> structure by changing strings ...
  • regress target) must be transform to mean shape coordination like this: regression_targets[i] = scale * regression_targets[i] * rotation;</li></ol>该提问来源于开源项目:soundsilence/Face...
  • RUN TestTwoHostsMultipleTenants_regress 2015/04/03 19:13:34 ovs-vsctl on node netplugin-node2: 2bfd5ce9-a922-48b3-9a76-65e929639b9d Manager "ptcp:6640" is_connected: true Bridge ...
  • <div><p>Put gpfdist's test and code under same directory. <p>Enhance pg_regress to call needed perl scripts from correct directory.</p><p>该提问来源于开源项目:greenplum-db/gpdb</p></div>
  • added bad_ram regress

    2021-01-10 11:02:53
    % python tests/regress/bad_ram.py Bad ram pointer 0x7f25ee400000 [1] 32327 abort (core dumped) python tests/regress/bad_ram.py </code></pre> <p>Effected code: <pre><code> C static ram_addr_t qemu_...
  • ospfd-regress:OpenBSD ospfd的回归测试
  • <div><ul><li>option -c to head(1) is not supported, use dd(1) ...<p>All regress tests pass on OpenBSD/amd64 5.8-current from Oct 2, 2015</p><p>该提问来源于开源项目:Parchive/par2cmdline</p></div>
  • matlab的regress函数

    千次阅读 2018-02-03 10:59:46
    在matlab中regress()函数可以进行回归分析,regress()函数主要用于线性回归,一元以及多元的。  regress()函数详解  [b,bint,r,rint,stats]=regress(y,X,alpha)  说明:  因变量数据向量y表示一...
  • <div><ol><li>add expected output files</li><li>add schedule file</li><li>use pg_regress to check results automatically</li><li>refactor gpcheckcloud regress shell script</li></ol> <p>Signed-off-by: ...
  • matlab 线性回归 regress

    2021-05-11 14:16:44
    [b,bint,r,rint,s]=regress(y,X,alpha) 输入: y:因变量(列向量), X:全一向量与自变量组成的矩阵 alpha 显著性水平 α\alphaα (缺省时设定为0.05) 输出: b:回归系数 bint:回归系数的的置信区间, r :残差 ...
  • <div><p>Both of the tests fail with <pre><code> # # Fatal error in ../../src/runtime/...on 32-bit, regress-542823 fails on 64-bit simulator also.</p><p>该提问来源于开源项目:v8mips/v8mips</p></div>
  • PostgreSQL regress test

    千次阅读 2015-08-14 12:29:05
    PostgresSQL regress test 最近看了下pg中的回归测试相关内容,现在将看到的内容记录下来。 1. 先来一个例子 [postgres@gorilla1 regress]$ make check make -C ../../../src/port all make[1]: Entering ...
  • Modelos_de_Regress-o:PIBIC项目
  • <p>This Pull Request ...s find and matching API</li><li><em>refactors capture methods using regress's capture group system</em> <- TODO</li></ul>该提问来源于开源项目:boa-dev/boa</p></div>
  • MATLAB 多元线性回归(regress

    千次阅读 2020-02-16 20:52:54
    MATLAB 多元线性回归(regress) 语法 b = regress(y,X) [b,bint] = regress(y,X) [b,bint,r] = regress(y,X) [b,bint,r,rint] = regress(y,X) [b,bint,r,rint,stats] = regress(y,X) [___] = regress(y,X,alpha) ...
  • <div><p>I have project with latest Rails 4 and Sprockets Rails 2.0.0.rc1, but when I execute <code>... So we regress GZip compression.</p><p>该提问来源于开源项目:rails/sprockets-rails</p></div>
  • regress 顾名思义,就是一元多元方程的的拟合,y=c1*x1+c2*x2....或者y=c1*x1^2+c2*x2^2+c3*x1*x2....等等形式 [b,BINT] = regress(Y,X) [b,BINT,R] = regress(Y,X) [b,BINT,R,RINT] = regress(Y,X) [b,BINT,R,...
  • <div><p>When running PRSice 2.2.6 with <code>--no-regress, I would expect all scores to be printed in the output file. However, I get only the score for thetop (most stringent) threshold, and all the ...

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