【正文】 thod of time series analysis applied in economy is mainly the analytical method of time series in a fixed time,such as Exponential Smoothing method,Moving Average method,Deposition of the time series and so the development of society,many uncertain elements impose influences on economy,which should be attached importance to 1970,Box and Jenkins proposed an analytical method of time series based on random theory which not only takes the theory of time series analysis to a new level but also promotes the preciseness of basic analytical models of time series are model and Based on time series theory to China from 1978 to 2022 the gross domestic product of three decades, based on the smooth of the data processing, model identification, parameter estimation, establish a time series model, and model testing, to determine more suitable model for autoregressive moving average model . Model of China39。s economy in the production of all final goods and services of value,it reflects the national and regional economic development and people39。利用 模型對??1,2I ??1,2RIM我國 2022—2022 年 GDP 作出預(yù)測并與實(shí)際值比較，結(jié)果表明相對誤差均在 3%之內(nèi)，預(yù)測模型良好，繼續(xù)利用 模型對我國未來 5 年的國內(nèi)生產(chǎn)總值做出預(yù)測。時(shí)間序列分析的基本模型有： 模型和 模型。隨著社會(huì)的發(fā)展，許多不確定因素在經(jīng)濟(jì)生活中的影響越來越大，必須引起人們的重視。時(shí)間序列預(yù)測方法則是通過時(shí)間序列的歷史數(shù)據(jù)揭示現(xiàn)象隨時(shí)間變化的規(guī)律，將這種規(guī)律延伸到未來，從而對該現(xiàn)象的未來做出預(yù)測。對其進(jìn)行分析及時(shí)準(zhǔn)確的預(yù)測具有重要的理論與現(xiàn)實(shí)意義。這個(gè)指標(biāo)把國民經(jīng)濟(jì)全部活動(dòng)的產(chǎn)出成果概括在一個(gè)極為簡明的統(tǒng)計(jì)數(shù)字之中，為評價(jià)和衡量國家經(jīng)濟(jì)狀況、經(jīng)濟(jì)增長趨勢及社會(huì)財(cái)富的經(jīng)濟(jì)表現(xiàn)提供了一個(gè)最為綜合的尺度?；跁r(shí)間序列模型的 GDP 預(yù)測摘 要國內(nèi)生產(chǎn)總值(GDP)是現(xiàn)代國民經(jīng)濟(jì)核算體系的核心指標(biāo)，是衡量一個(gè)國家綜合國力的重要指標(biāo)。國內(nèi)生產(chǎn)總值(Gross Domestic Product)是指在一定時(shí)期內(nèi)(一個(gè)季度或一年)，一個(gè)國家或地區(qū)的經(jīng)濟(jì)中所生產(chǎn)出的全部最終產(chǎn)品和勞務(wù)的價(jià)值，它反映國家和地區(qū)的經(jīng)濟(jì)發(fā)展及人民生活水平，常被公認(rèn)為衡量國家經(jīng)濟(jì)狀況的最佳指標(biāo)。可以說，它是影響經(jīng)濟(jì)生活乃至社會(huì)生活的最重要的經(jīng)濟(jì)指標(biāo)。 時(shí)間序列是指同一空間、不同時(shí)間某一現(xiàn)象的統(tǒng)計(jì)指標(biāo)數(shù)值按時(shí)間先后順序形成的一組動(dòng)態(tài)序列。傳統(tǒng)的時(shí)間序列分析方法在經(jīng)濟(jì)中的應(yīng)用，主要是確定性的時(shí)間序列分析方法，包括指數(shù)平滑法、移動(dòng)平均法、時(shí)間序列的分解等等。1970 年，Box 和 Jenkins 提出了以隨機(jī)理論為基礎(chǔ)的時(shí)間序列分析方法，使時(shí)間序列分析理論上升到了一個(gè)新的高度，預(yù)測的精度大大提高。 ARMIA本文基于時(shí)間序列理論，以我國 1978 年至 2022 年三十年的國內(nèi)生產(chǎn)總值為基礎(chǔ)，對數(shù)據(jù)進(jìn)行平穩(wěn)化處理、模型識別、參數(shù)估計(jì)，建立時(shí)間序列模型，并對模型進(jìn)行檢驗(yàn)，確定較適合模型為自回歸移動(dòng)平均模型 。??1,2ARIM 關(guān)鍵詞：時(shí)間序列，國內(nèi)生產(chǎn)總值， 模型， 模型ARIMTime Series Model for Forecasting GDP ABSTRACT Gross domestic product (GDP) is the modern heart of the System of National Accounts indicators,is a measure of a country an important indicator of overall national is defined as a certain period of time (one quarter or year),a country or region39。s living standards,a measure of a nation is often regarded as the best indicator of economic indicator in all the activities of the national economy39。s GDP forecast for ??1,2ARI20222022 and pared with the actual values, results showed that the relative error of 3%, the prediction model a good model to continue to forecast the gross domestic product of China in the next 5 years.KEY WORDS:Time series,Gross domestic product, model, model ARMIA目 錄摘 要 .....................................................................IABSTRACT .................................................................II1 引言 ....................................................................1 GDP 概述及其分析預(yù)測原因 ............................................1 時(shí)間序列分析法簡述 ..................................................2 本文的主要工作 ......................................................32 時(shí)間序列分析基本方法 ....................................................4 時(shí)間序列分析的預(yù)處理 ................................................4 差分運(yùn)算 ......................................................4 平穩(wěn)性檢驗(yàn) ....................................................4 時(shí)間序列基本模型 ....................................................6 自回歸模型 ....................................................6 移動(dòng)平均模型 ..................................................7 自回歸滑動(dòng)平均模型 ............................................7 ARIMA 模型建模步驟 .................................................8 數(shù)據(jù)平穩(wěn)化處理 ................................................8 模型識別 ......................................................8 參數(shù)估計(jì) ......................................................9 模型檢驗(yàn) ......................................................93 基于時(shí)間序列模型的 GDP 預(yù)測實(shí)例分析 ....................................10 我國 GDP 時(shí)間序列分析 ..............................................10 平穩(wěn)性檢查 ...................................................10 平穩(wěn)化處理 ...