| 中文 | 英文 |
| 调整的R^2 （确定系数） | adjusted R^2 |
| 调整系数 | adjustment coefficient |
| 调整系数矩阵 | adjustment coefficient matrix |
| 赤池信息准则（AIC） | Akaike’s information criterion (AIC) |
| 阿尔蒙分布滞后模型 | Almen distributed lag model |
| 阿尔蒙滞后 | Almon lags |
| 备择假设 | alternative hypothesis |
| 方差分析 | analysis of variance |
| 辅助变量 | ancillary variable |
| 近似协方差矩阵 | approximate covariance matrix |
| 近似正态分布 | approximate normal distribution |
| 自回归模型 | AR model |
| 自回归过程 | AR process |
| 自回归条件异方差模型 | ARCH model |
| 自回归移动平均模型 | ARMA model |
| 假定 | assumption |
| 渐近χ2分布 | asymptotic χ2 distribution |
| 渐近协方差矩阵 | asymptotic covariance matrix |
| 渐近分布 | asymptotic distribution |
| 渐近有效性 | asymptotic efficiency |
| 渐近性质 | asymptotic properties |
| 渐近抽样特性 | asymptotic sampling properties |
| 渐近设定 | asymptotic specification |
| 渐近标准误差 | asymptotic standard error |
| 渐近检验 | asymptotic test |
| 渐近检验统计量 | asymptotic test statistic |
| 渐近逼近 | asymptotically approximation |
| 渐近有效估计式 | asymptotically efficient estimator |
| 渐近无偏估计式 | asymptotically unbiased estimator |
| ADF检验，增项（增广）DF检验 | Augmented Dickey-Fuller test |
| AEG检验，增项（增广）EG检验 | Augmented Engle-Granger test |
| 自相关方程误差 | autocorrelated equation error |
| 自相关 | autocorrelation |
| 自相关函数 | autocorrelation function |
| 自协方差 | autocovariance |
| 自协方差函数 | autocovariance function |
| 自回归 | autoregression |
| 自回归条件异方差 | autoregressive conditional heteroscedasticity |
| 自回归分布滞后模型 | autoregressive distributed lag (ADL) model |
| 自回归单整移动平均（ARIMA）过程 | autoregressive integrated moving average process |
| 自回归（AR）摸型 | autoregressive model |
| 自回归移动平均（ARMA）过程 | autoregressive moving-average process |
| 自回归算子 | autoregressive operator |
| 辅助回归 | auxiliary regression |
| 平均值 | average |
| 行为方程 | behavioral equation |
| 贝拉－哈尔克（BJ）统计量 | Bera-Jarque statistic |
| 贝努利分布 | Bernoulli distribution |
| 最佳决策 | best decision |
| 最佳线性无偏估计式（BLUE） | best linear unbiased estimator (BLUE) |
| 最佳线性无偏预测 | best linear unbiased prediction |
| 最佳无偏估计式 | best unbiased estimator |
| 偏倚 | bias |
| 偏倚向量 | bias vector |
| 有偏估计式 | biased estimator |
| 二元选择模型 | binary choice model |
| 二项分布 | binomial distribution |
| 二元正态随机变量 | bivariate normal random variable |
| 自举法，靴襻法 | bootstrap procedure |
| 博克斯－考克斯变换 | Box-Cox transformation |
| 博克斯－詹金斯方法 | Box-Jenkins approach |
| 布罗施－帕甘检验 | Breusch-Pagan test |
| 布朗运动 | Brownian motion |
| 典型相关 | canonical correlation |
| 因果性 | causality |
| 中心极限定理 | central limit theorem |
| 特征方程 | characteristic equation |
| 特征根 | characteristic root |
| 特征向量 | characteristic vector |
| 卡埃方分布 | chi-square distribution |
| 古典统计学 | classical statistics |
| 柯布－道格拉斯生产函数 | Cobb-Douglas production function |
| 科克伦－奥克特方法 | Cochrane-Orcutt procedure |
| “概率极限”概念 | concept of “plim” |
| 条件推断 | conditional inference |
| 条件概率 | conditional probability |
| 条件概率密度函数 | conditional probability density function |
| 置信区间 | confidence interval |
| 一致性 | consistency |
| 一致估计式 | consistent estimator |
| 一致性检验 | consistent test |
| 消费函数 | consumption function |
| 同期相关 | contemporaneous correlation |
| 同期协方差矩阵 | contemporaneous covariance matrix |
| 同期扰动相关 | contemporaneous disturbance correlation |
| 同期独立随机回归自变量 | contemporaneous independent stochastic regressor |
| 连续映射理论 | continuous mapping theorem |
| 连续随机变量 | continuous random variable |
| 连续回归函数 | continuous regression function |
| 常规抽样理论 | conventional sampling theory |
| 依概率收敛 | converge in probability |
| 收敛 | convergence |
| 依分布收敛 | convergence in distribution |
| 相关 | correlation |
| 相关系数 | correlation coefficient |
| 相关矩阵 | correlation matrix |
| 相关图 | correlogram |
| 成本 | cost |
| 协方差 | covariance |
| 协方差矩阵 | covariance matrix |
| 协方差矩阵估计式 | covariance matrix estimator |
| 克拉美规则 | Cramér rule |
| 克拉美－拉奥不等式 | Cramér-Rao inequality |
| 克拉美－拉奥下界 | Cramér-Rao lower bound |
| 临界区域 | critical region |
| 临界值 | critical value |
| 截面数据 | cross-section data |
| 累积分布函数 | cumulative distribution function |
| 数据 | data |
| 数据生成过程（dgp） | date generation process |
| 数据标准化 | date normalization |
| 盲始模型 | dead-start model |
| 决策 | decision making |
| 决策规则 | decision rule |
| 决策规则选择 | decision rule choice |
| 决策理论 | decision theory |
| 演绎系统 | deductive system |
| 定义方程 | definitional equation |
| 解释程度 | degree of explanation |
| 自由度 | degree of freedom |
| 密度函数 | density function |
| 相依变量 | dependent variable |
| 设计矩阵 | design matrix |
| 检验方法 | detection methods |
| 方阵的行列式 | determinant of a square matrix |
| 确定系数，可决系数 | determination coefficient |
| 诊断校验 | diagnostic checking |
| 对角矩阵 | diagonal matrix |
| 对称矩阵的对角化 | diagonalization of a symmetric matrix |
| 差分 | difference |
| 差分方程 | difference equation |
| 离散随机变量 | discrete random variable |
| 离散样本空间 | discrete sample space |
| 离散随机过程 | discrete stochastic process |
| 非均衡误差 | disequilibrium error |
| 不相交集 | disjoint set |
| 分布滞后 | distributed lag |
| 分布滞后模型 | distributed lag model |
| 分布 | distribution |
| 分布函数 | distribution function |
| 分布理论 | distribution theory |
| 扰动协方差矩阵 | disturbance covariance matrix |
| 扰动方差 | disturbance variance |
| 位移项 | drift |
| 虚拟变量 | dummy variable |
| 虚拟变量估计式 | dummy variable estimator |
| DW（德宾—沃森）统计量 | Durbin-Watson statistic |
| DW（德宾—沃森）检验 | Durbin-Watson test |
| 动态模型 | dynamic model |
| 动态乘数 | dynamic multiplier |
| 动态回归 | dynamic regression |
| 动态联立方程 | dynamic simultaneous equation |
| 计量经济学，经济计量学 | econometrics |
| 经济变量 | economic variables |
| 经济学 | economics |
| 经济 | economy |
| 有效性 | efficiency |
| EG检验 | EG test |
| 特征值 | eigen value |
| 弹性 | elasticity |
| 椭圆 | ellipse |
| 空集 | empty set |
| 内生变量 | endogenous variable |
| EG两步估计量 | Engel-Granger (EG) two-step estimate |
| EG两步法 | Engel-Granger (EG) two-step method |
| 方程误差 | equation error |
| 方程识别 | equation identification |
| 均衡 | equilibrium |
| 均衡分析 | equilibrium analysis |
| 均衡条件 | equilibrium condition |
| 均衡乘子 | equilibrium multiplier |
| 均衡关系 | equilibrium relationship |
| 均衡状态 | equilibrium state |
| 遍历性 | ergodicity |
| 误差 | error |
| 误差分量 | error component |
| 误差修正机制 | error correction mechanism |
| 误差修正模型 | error correction model |
| 误差修正项 | error correction term |
| 误差平方和 | error sum of squares |
| 误差向量 | error vector |
| 估计量 | estimate |
| 估计 | estimation |
| 估计式 | estimator |
| 欧氏空间 | Euclidean space |
| 外生前定变量 | exogenous predetermined variable |
| 外生变量 | exogenous variable |
| 期望算子 | expectation operator |
| 期望值 | expected value |
| 试验 | experiment |
| 被解释变量 | explained variable |
| 解释变量 | explaining variable |
| 解释 | explanation |
| 指数分布 | exponential distribution |
| F分布 | F distribution |
| F统计量 | F statistic |
| F检验 | F test |
| 因子分解准则 | factorization criterion |
| 反馈 | feedback |
| 最终形式 | final form |
| 有限分布滞后模型 | finite distribution lag model |
| 有限非奇异矩阵 | finite nonsingular matrix |
| 有限多项式滞后 | finite polynomial lag |
| 有限抽样特性 | finite sampling property |
| 有限方差 | finite variance |
| 一阶自回归模型 | first-order autoregressive model |
| 一阶条件 | first-order condition |
| 一阶差分算子 | first-order difference operator |
| 一阶泰勒级数 | first-order Taylor series |
| 拟合值 | fitted value |
| 固定回归自变量 | fixed regressor |
| 预测区间 | forecast interval |
| 预测区域 | forecast region |
| 预测方差 | forecast variance |
| 预测 | forecasting |
| 频数，频率 | frequency |
| 完全信息估计 | full information estimation |
| 完全信息极大似然法 | full information maximum likelihood method |
| 函数形式 | function form |
| 函数空间 | function space |
| 泛函中心极限定理 | functional central limit theorem (FCLT) |
| 伽玛分布 | Gamma distribution |
| 伽玛函数 | Gamma function |
| 广义自回归条件异方差模型 | GARCH |
| 高斯白噪声 | Gaussian white noise |
| 高斯－马尔可夫定理 | Gauss-Markov theorem |
| 高斯－牛顿算法 | Gauss-Newton algorithm |
| 一般协方差矩阵 | general covariance matrix |
| 一般均衡 | general equilibrium |
| 一般线性假设 | general linear hypothesis |
| 一般线性统计模型 | general linear statistical model |
| 一般随机回归自变量模型 | general stochastic regressor model |
| “一般到特殊”方法 | general to special method |
| 广义自回归算子 | generalized autoregressive operator |
| 广义最小二乘法 | generalized least squares |
| 广义最小二乘估计 | generalized least squares estimation |
| 广义最小二乘估计式 | generalized least squares estimator |
| 广义最小二乘方法 | generalized least squares procedure |
| 广义最小二乘残差 | generalized least squares residual |
| 广义最小二乘规则 | generalized least squares rule |
| 几何滞后模型估计 | geometric lag model estimation |
| 总体极小值 | global minimum |
| 拟合优度 | goodness of fit |
| 格兰杰因果性 | Granger causality |
| 格兰杰因果性检验 | Granger causality test |
| 格兰杰非因果性 | Granger noncausality |
| 格兰杰定理 | Granger representation theorem |
| 增长率模型 | growth rate model |
| 豪斯曼设定检验 | Hausman specification test |
| 重（厚）尾 | heavy tail |
| 海赛矩阵 | Hessian matrix |
| 异方差误差 | heteroscedastic error |
| 异方差 | heteroscedasticity |
| 同一性 | homogeneity |
| 同方差误差 | homoscedastic error |
| 同方差 | homoscedasticity |
| 假设 | hypothesis |
| 假设检验 | hypothesis test |
| 同分布随机变量 | identically distributed random variable |
| 识别 | identification |
| 识别规则 | identification rules |
| 单位矩阵 | identity matrix |
| 压缩矩阵，影响矩阵 | impact matrix |
| 影响乘数矩阵 | impact multiplier matrix |
| 非一致性 | inconsistency |
| 错误约束 | incorrect restriction |
| 独立同一分布 | independent and identical distribution (IID) |
| 独立分布 | independent distribution |
| 独立事件 | independent event |
| 独立随机变量 | independent random variable |
| 独立随机回归自变量 | independent stochastic regressor |
| 独立变量 | independent variable |
| 间接最小二乘法 | indirect least squares |
| 不等式约束 | inequality restriction |
| 推断 | inference |
| 无限分布滞后 | infinite distributed lag |
| 无限累加算子 | infinite summation operator |
| 无限方差 | infinite variance |
| 有影响的观测值 | influential observation |
| 信息矩阵 | information matrix |
| 内积 | inner product |
| 新息过程 | innovation sequence |
| 投入产出关系 | input-output relationship |
| 工具变量 | instrumental variable |
| 工具变量估计 | instrumental variable estimation |
| 单整 | integration |
| 截距 | intercept |
| 区间估计 | interval estimation |
| 区间预测 | interval forecast |
| 不变性 | invariance |
| 逆矩阵 | inverse matrix |
| 信息矩阵的逆 | inverse of information matrix |
| 可逆性 | invertibility |
| 可逆移动平均过程 | invertible moving-average process |
| 投资 | investment |
| 迭代方法 | iterative procedure |
| 大折刀方法 | jackknife procedure |
| 雅可比变换 | Jacobian of the transformation |
| 联合置信区间 | joint confidence interval |
| 联合置信区域 | joint confidence region |
| 联合密度函数 | joint density function |
| 联合扰动向量 | joint disturbance vector |
| 联合假设检验 | joint hypothesis test |
| 联合区间估计 | joint interval estimation |
| 联合零（原）假设 | joint null hypothesis |
| 联合概率分布 | joint probability distribution |
| 联合被确定变量 | jointly determined variable |
| 恰好识别方程 | just identified equation |
| 核 | kernel |
| 凯恩斯消费函数 | Keynesian consumption function |
| 凯恩斯模型 | Keynesian model |
| 克莱因－戈德伯格消费函数 | Klein-Goldberger consumption |
| 克莱因－鲁滨效用函数 | Klein-Rubin utility function |
| 柯依克变换 | Koyck transformation |
| 克罗内克尔积 | Kronecker product |
| 库恩－塔克条件 | Kuhn-Tucker condition |
| 峰度，峭度 | kurtosis |
| 滞后 | lag |
| 滞后长度 | lag length |
| 滞后算子 | lag operator |
| 滞后权数 | lag weight |
| 滞后变量 | lagged variable |
| 拉格朗日乘数 | Lagrange multiplier |
| 拉格朗日乘子检验 | Lagrange multiplier test |
| 拉普拉斯展开 | Laplace expansion |
| 大样本特性 | large sample properties |
| 全概率定律 | law of total probability |
| 前导模型 | leading indication model |
| 最小绝对离差 | least absolute deviation |
| 最小绝对误差估计式 | least absolute error estimator |
| 最小平方偏倚 | least squares bias |
| 最小平方准则 | least squares criterion |
| 最小平方估计式 | least squares estimator |
| 最小平方法 | least squares procedure |
| 最小平方残差 | least squares residual |
| 最小平方规则 | least squares rule |
| 最小平方方差估计式 | least squares variance estimator |
| 左逆矩阵 | left-inverse matrix |
| 显著性水平 | level of significance |
| 杠杆率 | leverage |
| 似然函数 | likelihood function |
| 似然原理 | likelihood principle |
| 似然比原理 | likelihood ratio principle |
| 似然比统计量 | likelihood ratio statistic |
| 似然比检验 | likelihood ratio test |
| 线性代数 | linear algebra |
| 线性联系 | linear association |
| 线性相依 | linear dependency |
| 线性相依向量 | linear dependent vector |
| 线性等式约束 | linear equality restriction |
| 线性方程 | linear equation |
| 线性方程系统 | linear equation system |
| 线性估计式 | linear estimator |
| 线性形式 | linear form |
| 线性参数 | linear in parameter |
| 线性无关向量 | linear independent vector |
| 线性不等式假设 | linear inequality hypothesis |
| 线性不等式约束 | linear inequality restriction |
| 线性损失函数 | linear loss function |
| 线性算子 | linear operator |
| 线性概率模型 | linear probability model |
| 线性规划模型 | linear programming model |
| 线性约束 | linear restriction |
| 线性规则 | linear rule |
| 线性联立方程 | linear simultaneous equation |
| 线性统计模型 | linear statistical model |
| 线性变换 | linear transformation |
| 线性无偏估计式 | linear unbiased estimator |
| 线性 | linearity |
| 局部极小值 | local minima |
| 罗基斯迪随机变量 | logistic random variable |
| 罗基特（Logit）模型 | logit model |
| 对数似然函数 | log-likelihood function |
| 对数线性函数 | log-linear function |
| 长期效应 | long-run effect |
| 损失 | loss |
| 损失函数 | loss function |
| 下三角矩阵 | lower triangular matrix |
| 矩（M）估计式 | M estimator |
| 移动平均模型 | MA model |
| 宏观经济学 | macroeconomics |
| 边缘分布 | marginal distribution |
| 边缘概率密度函数 | marginal probability density function |
| 边际消费倾向 | marginal propensity to consume |
| 数理经济学 | mathematical economics |
| 数学期望 | mathematical expectation |
| 矩阵 | matrix |
| 矩阵分解 | matrix decomposition |
| 极大似然估计 | maximum likelihood estimation |
| 极大似然估计式 | maximum likelihood estimator |
| 极大似然法 | maximum likelihood method |
| 均值 | mean |
| 均方误差 | mean square error |
| 均方误差准则 | mean square error criterion |
| 均方误差矩阵 | mean square error matrix |
| 均值向量 | mean vector |
| 测量误差 | measurement error |
| 中位数 | median |
| 矩法 | method of moments |
| 极小极大准则 | minimax criterion |
| 使损失最小 | minimizing loss |
| 使风险最小 | minimizing risk |
| 最小绝对离差估计式 | minimum absolute deviation estimator |
| 最小方差 | minimum variance |
| 最小方差无偏估计 | minimum variance unbiased estimation |
| 错误设定 | misspecification |
| 混合估计 | mixed estimation |
| 众数 | mode |
| 模型 | model |
| 模型设定 | model specification |
| 模数 | module |
| 复数的模 | modulus of a complex number |
| 矩 | moment |
| 蒙特卡罗 | Monte Carlo |
| 蒙特卡罗数据 | Monte Carlo data |
| 蒙特卡罗试验 | Monte Carlo experiment |
| 蒙特卡罗模拟 | Monte Carlo simulation |
| 移动平均 | moving average |
| 移动平均（MA）模型 | moving average (MA) model |
| 移动平均过程 | moving average process |
| 移动平均表示法 | moving average representation |
| 移动平均季节过滤算子 | moving average seasonal filter |
| 多重共线性 | multicollinearity |
| 多项选择模型 | multinomial choice models |
| 多项分布 | multinomial distribution |
| 多元回归 | multiple regression |
| 多重解 | multiple solution |
| 多重时间序列分析 | multiple time-series analysis |
| 乘法 | multiplication |
| 乘子，乘数 | multiplier |
| 多元分布 | multivariate distribution |
| 多元函数 | multivariate function |
| 多元正态分布 | multivariate normal distribution |
| 多元正态随机变量 | multivariate normal random variable |
| 多元随机变量 | multivariate random variable |
| 多元t 分布 | multivariate t distribution |
| 互斥集 | mutually exclusive set |
| 自然共轭先验概率密度函数 | natural conjugate prior probability density function |
| 半负定矩阵 | negative semidefinite matrix |
| 嵌套 | nest |
| 牛顿－拉夫森算法和方法 | Newton-Raphson algorithm and method |
| 非线性函数 | nonlinear function |
| 参数非线性 | nonlinear in the parameter |
| 非线性最小平方法 | nonlinear least squares |
| 非线性最小平方估计 | nonlinear least squares estimation |
| 非线性似然函数 | nonlinear likelihood function |
| 非线性极大似然估计 | nonlinear maximum likelihood estimation |
| 非线性回归 | nonlinear regression |
| 非线性似不相关回归方程 | nonlinear seemingly unrelated regression equation |
| 非线性 | nonlinearity |
| 非负定矩阵 | nonnegative definite matrix |
| 非嵌套模型 | nonnested models |
| 非正态分布 | nonnormal distribution |
| 非正态误差 | nonnormal error |
| 非正定矩阵 | nonpositive definite matrix |
| 非纯量单位协方差矩阵 | nonscalar identity covariance matrix |
| 非奇异矩阵 | nonsingular matrix |
| 非平稳 | nonstationary |
| 非平稳过程 | nonstationary process |
| 非随机变量 | nonstochatic variable |
| 正态分布 | normal distribution |
| 正态分布理论 | normal distribution theory |
| 正态误差的检验 | normal error testing |
| 正态线性统计模型 | normal linear statistical model |
| 正态概率密度函数的核 | normal probability density function |
| 正态随机向量 | normal random vector |
| 正态变量 | normal variable |
| 正态向量 | normal vector |
| 标准化常数 | normalizing constant |
| 正态分布随机变量 | normally distribution random variable |
| 多余参数 | nuisance parameter |
| 零（原）假设 | null hypothesis |
| 零矩阵 | null matrix |
| 空集，零集 | null set |
| 可观测随机变量 | observable random variable |
| 可观测随机向量 | observable random vector |
| 观测值样本 | observation sample |
| 观测上的等价模型 | observationally equivalent model |
| 阶 | order |
| 阶条件 | order condition |
| 普通最小二乘法 | ordinary least squares |
| 正交矩阵 | orthogonal matrix |
| 正交向量 | orthogonal vector |
| 正交 | orthogonality |
| 标准正交线性统计模型 | orthonormal linear statistical model |
| 离群值 | outliers |
| 过度识别方程 | overidentified equation |
| 参数 | parameter |
| 参数估计 | parameter estimation |
| 参数方差 | parameter variance |
| 参数检验 | parametric test |
| 帕累托分布 | Pareto distribution |
| 局部调整分布滞后模型 | partial adjustment distributed lag model |
| 偏（局部）调整模型 | partial adjustment model |
| 偏自相关 | partial autocorrelation |
| 偏自相关系数 | partial autocorrelation coefficient |
| 偏自相关函数 | partial autocorrelation function |
| 偏相关 | partial correlation |
| 偏相关图 | partial correlogram |
| 偏导数 | partial derivative |
| 局部均衡 | partial equilibrium |
| 分块逆规则 | partitioned inverse rule |
| 完全多重共线性 | perfect multicollinearity |
| 长期收入假设 | permanent income hypothesis |
| 分段线性回归 | piecewise linear regression |
| 分段回归函数 | piecewise regression function |
| 点估计量 | point estimate |
| 点估计 | point estimation |
| 点估计式 | point estimator |
| 点估计式性质 | point estimator properties |
| 多项式 | polynomial |
| 多项式滞后 | polynomial lag |
| 多项式矩阵 | polynomial matrix |
| 合并数据 | pooling data |
| 合并模型 | pooling model |
| 合并模型选择 | pooling model selection |
| 合并时间序列 | pooling time series |
| 合并时间序列数据 | pooling time series data |
| 总体 | population |
| 正定矩阵 | positive definite matrix |
| 正定对称矩阵 | positive definite symmetric matrix |
| 半正定矩阵 | positive semidefinite matrix |
| 后验密度 | posterior density |
| 后验密度函数 | posterior density function |
| 后验分布 | posterior distribution |
| 后验信息 | posterior information |
| 后验均值 | posterior mean |
| 后验优势 | posterior odds |
| 后验优势比 | posterior odds ratio |
| 后验概率 | posterior probability |
| 后验概率密度函数 | posterior probability density function |
| 后验概率区域 | posterior probability region |
| 假设过程 | postulation process |
| 功效函数 | power function |
| 检验功效 | power of a test |
| 前定变量 | predetermined variable |
| 预测误差 | prediction error |
| 随机分量的预测 | prediction of random components |
| 预测精度 | prediction precision |
| 主分量模型 | principal components model |
| 先验协方差矩阵 | prior covariance matrix |
| 先验分布 | prior distribution |
| 先验均值 | prior mean |
| 先验概率 | prior probability |
| 先验概率密度函数 | prior probability density function |
| 先验概率区域 | prior probability region |
| 概率 | probability |
| 概率密度 | probability density |
| 概率分布 | probability distribution |
| 离散随机变量的概率分布 | probability distribution for discrete random variable |
| 概率分布函数 | probability distribution function |
| 概率测度 | probability measure |
| 概率单位（probit）模型 | probit model |
| 积矩 | product moment |
| 积矩量矩阵 | product moment matrix |
| 积算子 | product operator |
| 生产函数 | production function |
| 生产过程 | production process |
| 比例响应模型 | proportional response model |
| 伪样本数据 | pseudo sample data |
| 二次型 | quadratic form |
| 二次损失函数 | quadratic loss function |
| 二次矩阵 | quadratic matrix |
| 定量选择模型 | quantitative choice model |
| 定量因素 | quantitative factors |
| 定量信息 | quantitative information |
| 随机系数模型 | random coefficient model |
| 随机分量预测 | random component prediction |
| 随机误差 | random error |
| 随机试验 | random experiment |
| 随机变量 | random variable |
| 随机向量 | random vector |
| 随机向量分量 | random vector component |
| 随机游走 | random walk |
| 秩 | rank |
| 秩条件 | rank condition |
| 矩阵的秩 | rank of a matrix |
| 简化型 | reduced form |
| 简化型系数 | reduced form coefficient |
| 简化型扰动 | reduced form disturbance |
| 简化型方程 | reduced form equation |
| 简化型估计式 | reduced form estimator |
| 简化型模型 | reduced form model |
| 简化型参数 | reduced form parameter |
| 简化型参数估计 | reduced form parameters estimation |
| 回归 | regression |
| 回归诊断 | regression diagnostics |
| 回归模型 | regression model |
| 回归自变量矩阵 | regressor matrix |
| 回归自变量标准化 | regressor variable standardization |
| 正则性条件 | regularity condition |
| 拒绝域 | rejection region |
| 相对频率（数） | relative frequency |
| 再参数化 | reparameterization |
| 重复抽样 | repeated sampling |
| 再抽样方法 | resampling methods |
| 残差 | residual |
| 响应面 | response surface |
| 约束估计 | restricted estimation |
| 约束广义最小二乘方估计式 | restricted generalized least squares estimator |
| 约束最小二乘估计式 | restricted least squares estimator |
| 约束极大似然估计 | restricted maximum likelihood estimation |
| 规模报酬 | returns to scale |
| 岭回归 | ridge regression |
| 右逆矩阵 | right-inverse matrix |
| 风险 | risk |
| 风险函数 | risk function |
| 风险极小化 | risk minimization |
| 稳健（鲁棒）估计 | robust estimation |
| 微分规则 | rules of differentiation |
| 样本 | sample |
| 样本信息 | sample information |
| 样本中位数 | sample median |
| 样本观测值 | sample observation |
| 样本点 | sample point |
| 样本容量 | sample size |
| 样本空间 | sample space |
| 样本信息相结合 | sampleinformation combination |
| 抽样 | sampling |
| 抽样分布 | sampling distribution |
| 抽样试验 | sampling experiment |
| 抽样模型 | sampling model |
| 抽样模型的设定 | sampling model specification |
| 抽样精度 | sampling precision |
| 抽样过程 | sampling process |
| 抽样特性 | sampling property |
| 抽样理论 | sampling theory |
| 纯量乘法 | scalar multiplication |
| 得分检验 | score test |
| 季节协整 | seasonal cointegration |
| 季节数据 | seasonal data |
| 季节差分 | seasonal differencing |
| 季节虚拟变量 | seasonal dummy variable |
| 季节频率 | seasonal frequency |
| 季节单整 | seasonal integration |
| 季节单整检验 | seasonal integration test |
| 季节算子 | seasonal operator |
| 季节过程 | seasonal process |
| 季节单位根 | seasonal unit root |
| 季节性 | seasonality |
| 似不相关回归(SUR) | seemingly unrelated regression (SUR) |
| 似不相关回归方程 | seemingly unrelated regression equation |
| 似不相关回归估计量 | seemingly unrelated regression estimate |
| 似不相关回归估计式 | seemingly unrelated regression estimator |
| 选择矩阵 | selection matrix |
| 序贯方法检验 | sequential procedure testing |
| 联立方程组 | set of simultaneous equations |
| 集合论 | set theory |
| 方程组 | sets of equations |
| 线性方程组 | sets of linear equations |
| 线性统计模型组 | sets of linear statistical models |
| 短期 | short run |
| 短期预测 | short term forecasting |
| 显著性 | significance |
| 显著性检验 | significance test |
| 简单假设 | simple hypothesis |
| 简单线性回归 | simple linear regression |
| 模拟 | simulation |
| 联立方程统计模型 | simultaneous equation statistical model |
| 联立方程模型 | simultaneous equations model |
| 联立线性方程解 | simultaneous linear equation solution |
| 联立线性统计模型 | simultaneous linear statistical model |
| 联立统计模型 | simultaneous statistical model |
| 单一假设检验 | single hypothesis testing |
| 单一线性组合 | single linear combination |
| 单变量函数 | single variable function |
| 奇异矩阵 | singular matrix |
| 偏度 | skewness |
| 斜率系数 | slope coefficient |
| 斜率参数 | slope parameter |
| 小样本 | small sample |
| 小样本特性 | small sample properties |
| 多重共线性的解 | solution to multicollinearity |
| 设定误差 | specification error |
| 设定的检验 | specification testing |
| 样条函数 | spline function |
| 虚假相关 | spurious correlation |
| 虚假回归 | spurious regression |
| 离差平方 | squared deviation |
| 平方误差损失 | squared error loss |
| 方阵 | squared matrix |
| 堆积算子 | stacking operator |
| 标准差 | standard deviation |
| 标准误差 | standard error |
| 静态回归模型 | static regression model |
| 平稳性 | stationarity |
| 平稳 | stationary |
| 平稳自回归过程 | stationary autoregressive process |
| 平稳多变量过程 | stationary multivariate process |
| 平稳过程 | stationary process |
| 平稳随机过程 | stationary stochastic process |
| 统计量 | statistic |
| 统计决策理论 | statistical decision theory |
| 统计推断 | statistical inference |
| 统计模型 | statistical model |
| 统计模型选择 | statistical model selection |
| 统计模型设定 | statistical model specification |
| 统计检验 | statistical test |
| 统计检验的要素 | statistical test elements |
| 统计理论 | statistical theory |
| 随机假定 | stochastic assumption |
| 随机独立性 | stochastic independence |
| 随机线性回归模型 | stochastic linear regression model |
| 随机过程 | stochastic process |
| 随机回归自变量 | stochastic regressor |
| 随机约束 | stochastic restriction |
| 随机假设 | stochastically hypothesis |
| 随机约束估计式 | stochastically restricted estimator |
| 严平稳，强平稳 | strictly stationary |
| 结构变化 | structural change |
| 结构系数 | structural coefficient |
| 结构方程 | structural equation |
| 结构参数 | structural parameter |
| 结构位移检验 | structural shift test |
| “学生”随机变量 | student’s random variable |
| “学生”t分布 | student’s t distribution |
| 学生化残差 | studentized residual |
| 主观概率 | subjective probability |
| 主观概率分布 | subjective probability distribution |
| 子集 | subsets |
| 减法 | subtraction |
| 充分性 | sufficiency |
| 充分条件 | sufficient condition |
| 充分秩条件 | sufficient rank condition |
| 充分统计量 | sufficient statistic |
| 平方和 | sum of square |
| 离差平方和 | sum of squares deviation |
| 求和算子 | summation operator |
| 超一致性 | super consistent |
| 供给函数 | supply function |
| 似不相关（SUR）估计式 | SUR estimator |
| 开关回归模型 | switching regression model |
| 对称矩阵 | symmetric matrix |
| 联立线性方程模型 | system of simultaneous linear equation |
| 联立关系系统 | system of simultaneous relations |
| 系统变参数模型 | systematically varying parameter model |
| t 统计量 | t statistic |
| t 检验 | t test |
| 尾部概率 | tail probability |
| 泰勒级数近似 | Taylor series approximation |
| 检验水平 | test level |
| 检验统计量 | test statistic |
| 异方差检验 | testing for heteroscedasticity |
| 虚拟变量系数检验 | testing of coefficients of dummy variable |
| 理论模型 | theoretical model |
| 厚尾 | thick tail |
| 三阶段最小平方（3SLS）估计式 | three-stage least squares (3SLS) estimator |
| 时间序列 | time series |
| 时间序列分析 | time series analysis |
| 托毕特 (Tobit) 回归模型 | Tobit regression model |
| 迹 | trace |
| 矩阵的迹 | trace of a matrix |
| 方阵的迹 | trace of a square matrix |
| 变换 | transformation |
| 变换矩阵 | transformation matrix |
| 变换参数 | transformation parameter |
| 转换率 | transformation rate |
| 变换观测值 | transformed observation |
| 矩阵的转置 | transpose of a matrix |
| 趋势 | trend |
| 截尾样本 | truncated sample |
| 两个线性组合 | two linear combinations |
| 两段最小二乘法 | two-stage least squares |
| 两阶段最小平方估计式 | two-stage least squares estimator |
| 两阶段最小平方法 | two-stage least-squares procedure |
| 两步估计 | two-step estimation |
| 第I类错误 | type I error |
| 第II类错误 | type II error |
| 无偏估计式 | unbiased estimator |
| 无偏性 | unbiasedness |
| 无条件推断 | unconditional inference |
| 无条件均方误差准则 | unconditional mean squared error criterion |
| 不可识别 | unidentification |
| 单位根检验 | unit root test |
| 未知协方差矩阵 | unknown covariance matrix |
| 未知协方差矩阵的估计 | unknown covariance matrix estimation |
| 未知分布方差 | unknown distribution variance |
| 未知参数 | unknown parameter |
| 不可观测的随机误差 | unobservable random error |
| 不可观测的随机变量 | unobservable random variable |
| 不可观测的随机向量 | unobservable random vector |
| 不相关回归 | unrelated regression |
| 无约束有限分布滞后 | unrestricted finite distributed lags |
| 无约束最小二乘估计式 | unrestricted least squares estimator |
| 无约束极大似然估计式 | unrestricted maximum likelihood estimator |
| 无约束参数空间 | unrestricted parameter space |
| VAR过程 | VAR process |
| VAR过程估计 | VAR process estimation |
| VAR过程设定 | VAR process specification |
| 变量 | variable |
| 线性变量 | variable linearity |
| 方差 | variance |
| 方差分量的估计 | variance components estimation |
| 方差协方差矩阵 | variance covariance matrix |
| 方差估计 | variance estimation |
| 方差膨胀因子 | variance inflation factor |
| 变参数模型 | varying parameter model |
| 向量 | vector |
| 向量自回归预测 | vector autoregressive forecasting |
| 向量自回归（VAR）模型 | vector autoregressive model |
| 向量自回归模型扩展 | vector autoregressive model extensions |
| 向量自回归移动平均（VARMA）过程 | vector autoregressive moving average (VARMA) process |
| 向量自回归过程 | vector autoregressive process |
| 向量误差修正（VEC）模型 | vector error correction model |
| 向量随机过程 | vector stochastic process |
| 向量白噪声 | vector white noise |
| 向量化 | vectorization |
| 矩阵的向量化 | vectorization of a matrix |
| 波动 | volatility |
| 沃尔德统计量 | Wald statistic |
| 弱平稳 | weak stationary |
| 加权平均 | weighted average |
| 加权最小二乘法 | weighted least squares |
| 白噪声 | white noise |
| 维纳分布 | Wiener distribution |
| 维纳过程 | Wiener process |
| 零系数 | zero coefficient |
| 零约束 | zero restriction |
